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Audren, Hervé. "On multi-contact dynamic motion using reduced models." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTS012/document.
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Pour les robots marcheurs, c'est à dire bipèdes, quadrupèdes, hexapodes, etc... la notion de stabilité est primordiale. En effet, ces robots possèdent une base flottante sous-actuée : il leur faut prendre appui sur l'environnement pour se mouvoir. Toutefois, cette caractéristique les rend vulnérables: ils peuvent tomber. Il est donc indispensable de pouvoir différencier un mouvement stable d'un mouvement non-stable. Dans cette thèse, la stabilité est considérée du point de vue d'un modèle réduit au Centre de Masse (ou Centre de Gravité). Nous montrons dans un premier temps comment calculer la zone de stabilité de ce modèle dans le cas statique. Bien que cette région soit un objet purement géométrique, nous montrons qu'elle dépend des forces de contact admissibles. Ensuite, nous montrons qu'introduire la notion de robustesse, c'est à dire une marge d'incertitude sur les accélérations (ou les forces de contacts) transforme la forme plane du cas statique en un volume tridimensionnel. Afin de calculer cette forme, nous présentons de nouveaux algorithmes récursifs. Nous appliquons ensuite des algorithmes provenant de l'infographie qui permettent de déformer continûment ces objets géométriques. Cette transformation nous permet d'approximer des changements dans les variables influençant ces formes. Calculer le volume de stabilité explicitement nous permet de découpler les accélérations des positions du CdM, ce qui nous permet de formuler un problème de contrôle prédictif linéaire. Nous proposons aussi une autre formulation linéaire qui, au prix de calculs plus coûteux, permet d'exploiter pleinement la dynamique du robot. Enfin, nous appliquons ces résultats dans une approche hiérarchique qui nous permet de générer des mouvements du corps complet du robot, aussi bien sur une véritable plateforme humanoïde qu'en simulation<br>In the context of legged robotics, stability (or equilibrium) is of the utmost importance. Indeed, as legged robots have a non-actuated floating base they can fall. To avoid falling, we must be able to tell apart stable from non-stable motion. This thesis approaches stability from a reduced model point-of-view: our main interest is the Center of Mass. We show how to compute stability regions for this reduced model, at first based on purely static stability. Although purely geometrical in nature, we show how they depend on the admissible contact forces. Then, we show that taking into account robustness, in the sense of acceleration (or contact forces) affordances transforms the usual two-dimensional stability region into a three dimensional one. To compute this shape, we introduce novel recursive algorithms. We show how we can apply computer graphics techniques for shape morphing in order to continuously deform the aforementioned regions. This allows us to approximate changes in the parameters of those shapes, but also to interpolate between shapes. Finally, we exploit the effective decoupling offered by the explicit computation of the stability polyhedron to formulate a linear, minimal jerk model-predictive control problem. We also propose another linear MPC problem that exploits more of the available dynamics, but at an increased computational cost. We then adopt a hierarchical approach, and use those CoM results as input to our whole-body controller. Results are demonstrated on real hardware and in simulation
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Alaya, Oussama, and Maik Fiedler. "Optimal pressure control using switching solenoid valves." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-200545.
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This paper presents the mathematical modeling and the design of an optimal pressure tracking controller for an often used setup in pneumatic applications. Two pneumatic chambers are connected with a pneumatic tube. The pressure in the second chamber is to be controlled using two switching valves connected to the first chamber and based on the pressure measurement in the first chamber. The optimal control problem is formulated and solved using the MPC framework. The designed controller shows good tracking quality, while fulfilling hard constraints, like maintaining the pressure below a given upper bound.
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Enes, Aaron R. "Shared control of hydraulic manipulators to decrease cycle time." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37251.
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This thesis presents a technique termed Blended Shared Control, whereby a human operator's commands are merged with the commands of an electronic agent in real time to control a manipulator. A four degree-of-freedom hydraulic excavator is used as an application example, and two types of models are presented: a fully dynamic model incorporating the actuator and linkage systems suitable for high-fidelity user studies, and a reduced-order velocity-constrained kinematic model amenable for real-time optimization. Intended operator tasks are estimated with a recursive algorithm; the task is optimized in real time; and a command perturbation is computed which, when summed with the operator command, results in a lower task completion time. Experimental results compare Blended Shared Control to other types of controllers including manual control and haptic feedback. Trials indicate that Blended Shared Control decreases task completion time when compared to manual operation.
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Dyson, Matthew. "Selecting optimal cognitive tasks for control of a brain computer interface." Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.528844.
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Francioni, Marco. "Modeling and optimal flight control of a foiling dinghy." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23367/.
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This Master Thesis illustrates the physics behind the mathematical model of a foiling dinghy to be used in a model-based autopilot architecture, and the multiple frames of references needed for an exhaustive force description. Using the modeled foiling boat, we performed the non-trivial task of finding meaningful trim setpoints, which were then used throughout the simulations. We applied Optimal Control theories to achieve stability and control of a foiling dinghy with a movable crew at different trim settings
and various environmental parameters, such as wind speed and
sea state, both stationary and time-varying. We developed a prototype of a gain scheduler for the closed-loop to perform tack and jibes maneuvers in multiple environments, and compared the stability and parameters sensitivity of different closed feedback loop architectures, both in a straight line and maneuvering performance.
The maneuvering performances were established with extensive
ad-hoc simulations to properly characterize the behavior of the architecture, while the straight-line response and parameter variation sensitivity was determined through Monte Carlo simulations.
At the end of this paperwork, the two best performing closed-loop architectures proposed were compared to determine which one would be the more promising for a practical application.
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Gaid, MEMB, AS Cela, and Y. Hamam. "Optimal Real-Time Scheduling of Control Tasks with State Feedback Resource Allocation." IEEE Transactions on Control Systems Technology, 2009. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1001370.
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Abstract—This paper proposes a new approach for the optimal
integrated control and real-time scheduling of control tasks.
First, the problem of the optimal integrated control and nonpreemptive
off-line scheduling of control tasks in the sense of
the H2 performance criterion is addressed. It is shown that this
problem may be decomposed into two sub-problems. The first
sub-problem aims at finding the optimal non-preemptive off-line
schedule, and may be solved using the branch and bound method.
The second sub-problem uses the lifting technique to determine
the optimal control gains, based on the solution of the first
sub-problem. Second, an efficient on-line scheduling algorithm
is proposed. This algorithm, called Reactive Pointer Placement
(RPP) scheduling algorithm, uses the plant state information to
dispatch the computational resources in a way that improves
control performance. Control performance improvements as well
as stability guarantees are formally proven. Finally, simulations
as well as experimental results are presented in order to illustrate
the effectiveness of the proposed approach.
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Basilewitsch, Daniel [Verfasser]. "Optimal control of quantum information tasks in open quantum systems / Daniel Basilewitsch." Kassel : Universitätsbibliothek Kassel, 2021. http://d-nb.info/1232368407/34.
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Perundurai, Rajasekaran Siddharthan. "Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/1205.
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"This thesis focuses on two key problems in reinforcement learning: How to design reward functions to obtain intended behaviors in autonomous systems using the learning-based control? Given complex mission specification, how to shape the reward function to achieve fast convergence and reduce sample complexity while learning the optimal policy? To answer these questions, the first part of this thesis investigates inverse reinforcement learning (IRL) method with a purpose of learning a reward function from expert demonstrations. However, existing algorithms often assume that the expert demonstrations are generated by the same reward function. Such an assumption may be invalid as one may need to aggregate data from multiple experts to obtain a sufficient set of demonstrations. In the first and the major part of the thesis, we develop a novel method, called Non-parametric Behavior Clustering IRL. This algorithm allows one to simultaneously cluster behaviors while learning their reward functions from demonstrations that are generated from more than one expert/behavior. Our approach is built upon the expectation-maximization formulation and non-parametric clustering in the IRL setting. We apply the algorithm to learn, from driving demonstrations, multiple driver behaviors (e.g., aggressive vs. evasive driving behaviors). In the second task, we study whether reinforcement learning can be used to generate complex behaviors specified in formal logic — Linear Temporal Logic (LTL). Such LTL tasks may specify temporally extended goals, safety, surveillance, and reactive behaviors in a dynamic environment. We introduce reward shaping under LTL constraints to improve the rate of convergence in learning the optimal and probably correct policies. Our approach exploits the relation between reward shaping and actor-critic methods for speeding up the convergence and, as a consequence, reducing training samples. We integrate compositional reasoning in formal methods with actor-critic reinforcement learning algorithms to initialize a heuristic value function for reward shaping. This initialization can direct the agent towards efficient planning subject to more complex behavior specifications in LTL. The investigation takes the initial step to integrate machine learning with formal methods and contributes to building highly autonomous and self-adaptive robots under complex missions."
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Smit, Willem Jacobus. "The optimal design of a planar Stewart platform for prescribed machining tasks." Diss., Pretoria : [s.n.], 2000. http://upetd.up.ac.za/thesis/available/etd-01122007-134416/.
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Bountourelis, Theologos. "Efficient pac-learning for episodic tasks with acyclic state spaces and the optimal node visitation problem in acyclic stochastic digaphs." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28144.
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Thesis (M. S.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Reveliotis, Spyros; Committee Member: Ayhan, Hayriye; Committee Member: Goldsman, Dave; Committee Member: Shamma, Jeff; Committee Member: Zwart, Bert.
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Euler, Juliane [Verfasser], Oskar von [Akademischer Betreuer] Stryk, and Rui [Akademischer Betreuer] Rocha. "Optimal Cooperative Control of UAVs for Dynamic Data-Driven Monitoring Tasks / Juliane Euler ; Oskar von Stryk, Rui Rocha." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2018. http://d-nb.info/1151638811/34.
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Welch, Torrence David Jesse. "A feedback model for the evaluation of the adaptive changes to temporal muscle activation patterns following postural disturbance." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/29674.
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Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Ting, Lena; Committee Member: Chang, Young-Hui; Committee Member: Nichols, T. Richard; Committee Member: Schumacher, Eric; Committee Member: Thoroughman, Kurt. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Anisi, David A. "Online trajectory planning and observer based control." Licentiate thesis, Stockholm : Optimization and systems theory, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4153.
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Phillips-Grafflin, Calder. "Enabling Motion Planning and Execution for Tasks Involving Deformation and Uncertainty." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-dissertations/307.
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"A number of outstanding problems in robotic motion and manipulation involve tasks where degrees of freedom (DoF), be they part of the robot, an object being manipulated, or the surrounding environment, cannot be accurately controlled by the actuators of the robot alone. Rather, they are also controlled by physical properties or interactions - contact, robot dynamics, actuator behavior - that are influenced by the actuators of the robot. In particular, we focus on two important areas of poorly controlled robotic manipulation: motion planning for deformable objects and in deformable environments; and manipulation with uncertainty. Many everyday tasks we wish robots to perform, such as cooking and cleaning, require the robot to manipulate deformable objects. The limitations of real robotic actuators and sensors result in uncertainty that we must address to reliably perform fine manipulation. Notably, both areas share a common principle: contact, which is usually prohibited in motion planners, is not only sometimes unavoidable, but often necessary to accurately complete the task at hand. We make four contributions that enable robot manipulation in these poorly controlled tasks: First, an efficient discretized representation of elastic deformable objects and cost function that assess a ``cost of deformation' for a specific configuration of a deformable object that enables deformable object manipulation tasks to be performed without physical simulation. Second, a method using active learning and inverse-optimal control to build these discretized representations from expert demonstrations. Third, a motion planner and policy-based execution approach to manipulation with uncertainty which incorporates contact with the environment and compliance of the robot to generate motion policies which are then adapted during execution to reflect actual robot behavior. Fourth, work towards the development of an efficient path quality metric for paths executed with actuation uncertainty that can be used inside a motion planner or trajectory optimizer."
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Anisi, David A. "On Cooperative Surveillance, Online Trajectory Planning and Observer Based Control." Doctoral thesis, KTH, Optimeringslära och systemteori, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9990.
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The main body of this thesis consists of six appended papers. In the first two, different cooperative surveillance problems are considered. The second two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.In Papers A and B, a combinatorial optimization based framework to cooperative surveillance missions using multiple Unmanned Ground Vehicles (UGVs) is proposed. In particular, Paper A considers the the Minimum Time UGV Surveillance Problem (MTUSP) while Paper B treats the Connectivity Constrained UGV Surveillance Problem (CUSP). The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a waypoint-path and such that the time for executing the search in parallel is minimized. The connectivity constrained formulation extends the MTUSP by additionally requiring the induced information graph to be kept recurrently connected at the time instants when the UGVs perform the surveillance mission. In these two papers, the NP-hardness of both these problems are shown and decomposition techniques are proposed that allow us to find an approximative solution efficiently in an algorithmic manner.Paper C addresses the problem of designing a real time, high performance trajectory planner for an aerial vehicle that uses information about terrain and enemy threats, to fly low and avoid radar exposure on the way to a given target. The high-level framework augments Receding Horizon Control (RHC) with a graph based terminal cost that captures the global characteristics of the environment. An important issue with RHC is to make sure that the greedy, short term optimization does not lead to long term problems, which in our case boils down to two things: not getting into situations where a collision is unavoidable, and making sure that the destination is actually reached. Hence, the main contribution of this paper is to present a trajectory planner with provable safety and task completion properties. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In Paper D, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example.In Paper E, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotic systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors. Finally, in Paper F, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. Moreover, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature.<br>QC 20100622<br>TAIS, AURES
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Blagouchine, Iaroslav. "Modélisation et analyse de la parole : Contrôle d’un robot parlant via un modèle interne optimal basé sur les réseaux de neurones artificiels. Outils statistiques en analyse de la parole." Thesis, Aix-Marseille 2, 2010. http://www.theses.fr/2010AIX26666.
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Cette thèse de doctorat traite les aspects de la modélisation et de l'analyse de la parole, regroupés sous le chapeau commun de la qualité. Le premier aspect est représenté par le développement d'un modèle interne de contrôle de la production de la parole ; le deuxième, par le développement des outils pour son analyse. Un modèle interne optimal sous contraintes est proposé pour le contrôle d'un robot parlant, basé sur l'hypothèse du point d'équilibre (EPH, modèle-lambda). Ce modèle interne se repose sur le principe suivant : les mouvements du robot sont produits de telle façon que la longueur du chemin, parcouru dans l'espace interne des commandes motrices lambda, soit minimale, sous certaines contraintes liées à l'espace externe. L'aspect mathématique du problème conduit au problème géodésique généralisé, un problème relevant du calcul variationnel, dont la solution exacte analytique est assez complexe. En utilisant certains résultats empiriques, une solution approximative est enfin développée et implémentée. La solution du problème donne des résultats intéressants et prometteurs, et montre que le modèle interne proposé permet d'atteindre une certaine réalité de la production de la parole ; notamment, des similitudes entre la parole réelle et celle produite par le robot sont constatées. Puis, dans un but d'analyser et de caractériser le signal de parole, plusieurs méthodes d'analyse statistique sont développées. Elles sont basées sur les statistiques d'ordre supérieurs et sur l'entropie discrète normalisée. Dans ce cadre, nous avons également élaboré un estimateur non-biaisée et efficace du cumulant d'ordre quatre, en deux versions bloc et adaptative<br>This Ph.D. dissertation deals with speech modeling and processing, which both share the speech quality aspect. An optimum internal model with constraints is proposed and discussed for the control of a biomechanical speech robot based on the equilibrium point hypothesis (EPH, lambda-model). It is supposed that the robot internal space is composed of the motor commands lambda of the equilibrium point hypothesis. The main idea of the work is that the robot movements, and in particular the robot speech production, are carried out in such a way that, the length of the path, traveled in the internal space, is minimized under acoustical and mechanical constraints. Mathematical aspect of the problem leads to one of the problems of variational calculus, the so-called geodesic problem, whose exact analytical solution is quite complicated. By using some empirical findings, an approximate solution for the proposed optimum internal model is then developed and implemented. It gives interesting and challenging results, and shows that the proposed internal model is quite realistic; namely, some similarities are found between the robot speech and the real one. Next, by aiming to analyze speech signals, several methods of statistical speech signal processing are developed. They are based on higher-order statistics (namely, on normalized central moments and on the fourth-order cumulant), as well as on the discrete normalized entropy. In this framework, we also designed an unbiased and efficient estimator of the fourth-order cumulant in both batch and adaptive versions
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Palagachev, Konstantin [Verfasser], Matthias [Akademischer Betreuer] Gerdts, Matthias [Gutachter] Gerdts, and Sebastian [Gutachter] Sager. "Mixed-Integer Optimal Control and Bilevel Optimization: Vanishing Constraints and Scheduling Tasks / Konstantin Palagachev ; Gutachter: Matthias Gerdts, Sebastian Sager ; Akademischer Betreuer: Matthias Gerdts ; Universität der Bundeswehr München, Fakultät für Luft- und Raumfahrttechnik." Neubiberg : Universitätsbibliothek der Universität der Bundeswehr München, 2017. http://d-nb.info/1172216533/34.
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Sage, Kingsley. "Task based visual control." Thesis, University of Sussex, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439890.
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Pavlic, Theodore Paul. "Design and Analysis of Optimal Task-Processing Agents." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1281462093.
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BerovicÌ, Daniel Philip. "Optimal hybrid control." Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.408766.
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Boucher, Randy. "Galerkin optimal control." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/44526.
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Approved for public release; distribution is unlimited<br>A Galerkin-based family of numerical formulations is presented for solving nonlinear optimal control problems. This dissertation introduces a family of direct methods that calculate optimal trajectories by discretizing the system dy-namics using Galerkin numerical techniques and approximate the cost function with Gaussian quadrature. In this numerical approach, the analysis is based on L2-norms. An important result in the theoretical foundation is that the feasibility and consistency theorems are proved for problems with continuous and/or piecewise continuous controls. Galerkin methods may be formulated in a number of ways that allow for efficiency and/or improved accuracy while solving a wide range of optimal control problems with a variety of state and control constraints. Numerical formula-tions using Lagrangian and Legendre test functions are derived. One formulation allows for a weak enforcement of boundary conditions, which imposes end conditions only up to the accuracy of the numerical approximation itself. Additionally, the multi-scale formulation can reduce the dimension of multi-scale optimal control problems, those in which the states and controls evolve on different timescales. Finally, numerical examples are shown to demonstrate the versatile nature of Galerkin optimal control.
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Liu, Chialun. "Hierarchical control in task switching." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:5dc1f9d4-fbfd-4652-9e1e-bc1b544c7a65.
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Human flexible behaviour is often seen in everyday life tasks. These tasks (e.g., making coffee) are composed of actions (e.g., pouring sugar) that are typically nested within a large task structures made of superordinate components and nested subcomponents. Task switching has been adopted widely as an effective tool to explore the mechanisms of flexible behaviour and can be easily adapted to real-life situations. The core hypothesis explored in this thesis was that there might be another level of control that is responsible for coordinating and scheduling actions in task switching, which I label "meta-control". My first project aimed to establish robust behavioural evidence of meta-control. To test this hypothesis, switching efficiency was treated as a measure of meta-control influence. In a novel design, participants' beliefs about switch probability were manipulated through explicit instruction, allowing manipulation of meta-level control independent of the specific sequence of tasks required. The first three behavioural experiments demonstrated behaviorally that instructions influenced the efficiency of switching even when low-level (bottom-up) experience was matched, and that this effect was motivation-dependent. In follow-up studies, this meta-control influence was found to bias voluntary task selection. Two EEG studies aimed to characterize the level at which instruction affected processing. Motor and task levels were examined with lateralized motor potentials and oscillatory alpha power, respectively. Effects of instruction only existed on alpha power. Overall, the results suggest that expectancy prompts the adoption of distinct control modes across sequences of trials. The second project explored meta-control in a task switching paradigm with a hierarchical task structure in very short (2-4 trial) sequences that were preceded by instructions about switch frequency or switch position. The experiments focused on the benefits and costs of sequence structure, based on the hypothesis that trial sequences are treated as coherent units. Three behavioural studies were conducted for testing this hypothesis. The first utilized instructions about switch frequency to test for sequence transition effects and their influence on switching performance at the trial level. In two subsequent experiments, instructions made explicit the position of a task switch. The results confirmed that instructions about switch position helped participants to build useful sequence representations, and that alternating between sequences influenced trial-level switch processes. Generally, sequence representations have a persisting influence across trials and a pronounced impact at the first trial position of sequences. The experiments in this thesis provide evidence of meta-control in task switching. The first conclusion is that meta-control can be studied with the novel experimental design introduced in this thesis and was found to be reward dependent. The second conclusion is that meta-control acts as a set of parameters that can modulate the mode of control in a sustained way across trials.
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Bast, Holger. "Provably optimal scheduling of similar tasks." [S.l. : s.n.], 2000. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10976167.
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Karasakal, Orhan. "Optimal Air Defense Strategies For A Naval Task Group." Phd thesis, Ankara : METU, 2004. http://etd.lib.metu.edu.tr/upload/12604699/index.pdf.
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Thesis (Ph. D.)--Middle East Technical University, 2004.<br>Keywords: Air Defense, Naval Task Group, Formation, Weapon Target Allocation Problem, Military Operations Research, Quadratic Assignment, Location.
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Adikarapatti, Vikramvarun Kannan. "OPTIMAL EEG CHANNELS AND RHYTHM SELECTION FOR TASK CLASSIFICATION." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1176482808.
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Shao, Cheng. "Biologically-inspired optimal control." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/3102.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.<br>Thesis research directed by: Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Stötzner, Ailyn. "Optimal Control of Thermoviscoplasticity." Universitätsverlag der Technischen Universität Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A31887.
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This thesis is devoted to the study of optimal control problems governed by a quasistatic, thermoviscoplastic model at small strains with linear kinematic hardening, von Mises yield condition and mixed boundary conditions. Mathematically, the thermoviscoplastic equations are given by nonlinear partial differential equations and a variational inequality of second kind in order to represent the elastic, plastic and thermal effects.
Taking into account thermal effects we have to handle numerous mathematical challenges during the analysis of the thermoviscoplastic model, mainly due to the low integrability of the nonlinear terms on the right-hand side of the heat equation. One of our main results is the existence of a unique weak solution, which is proved by means of a fixed-point argument and by employing maximal parabolic regularity theory. Furthermore, we define the related control-to-state mapping and investigate properties of this mapping such as boundedness, weak continuity and local Lipschitz continuity. Another major result is the finding that the mapping is Hadamard differentiable; a main ingredient is the reformulation of the variational inequality, the so called viscoplastic flow rule, as a Banach space-valued ordinary differential equation with non-differentiable right-hand side. Subsequently, we consider an optimal control problem governed by thermoviscoplasticity and show the existence of a minimizer. Finally, close this thesis with numerical examples.<br>Diese Arbeit ist der Untersuchung von Optimalsteuerproblemen gewidmet, denen ein quasistatisches, thermoviskoplastisches Model mit kleinen Deformationen, mit linearem kinematischen Hardening, von Mises Fließbedingung und gemischten Randbedingungen zu Grunde liegt. Mathematisch werden thermoviskoplastische Systeme durch nichtlineare partielle Differentialgleichungen und eine variationelle Ungleichung der zweiten Art beschrieben, um die elastischen, plastischen und thermischen Effekte abzubilden.
Durch die Miteinbeziehung thermischer Effekte, treten verschiedene mathematische Schwierigkeiten während der Analysis des thermoviskoplastischen Systems auf, die ihren Ursprung hauptsächlich in der schlechten Regularität der nichtlinearen Terme auf der rechten Seite der Wärmeleitungsgleichung haben. Eines unserer Hauptresultate ist die Existenz einer eindeutigen schwachen Lösung, welches wir mit Hilfe von einem Fixpunktargument und unter Anwendung von maximaler parabolischer Regularitätstheorie beweisen. Zudem definieren wir die entsprechende Steuerungs-Zustands-Abbildung und untersuchen Eigenschaften dieser Abbildung wie die Beschränktheit, schwache Stetigkeit und lokale Lipschitz Stetigkeit. Ein weiteres wichtiges Resultat ist, dass die Abbildung Hadamard differenzierbar ist; Hauptbestandteil des Beweises ist die Umformulierung der variationellen Ungleichung, der sogenannten viskoplastischen Fließregel, als eine Banachraum-wertige gewöhnliche Differentialgleichung mit nichtdifferenzierbarer rechter Seite. Schließlich runden wir diese Arbeit mit numerischen Beispielen ab.
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Pfeiffer, Laurent. "Sensitivity analysis for optimal control problems. Stochastic optimal control with a probability constraint." Palaiseau, Ecole polytechnique, 2013. https://pastel.hal.science/docs/00/88/11/19/PDF/thesePfeiffer.pdf.
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Cette thèse est divisée en deux parties. Dans la première partie, nous étudions des problèmes de contrôle optimal déterministes avec contraintes et nous nous intéressons à des questions d'analyse de sensibilité. Le point de vue que nous adoptons est celui de l'optimisation abstraite; les conditions d'optimalité nécessaires et suffisantes du second ordre jouent alors un rôle crucial et sont également étudiées en tant que telles. Dans cette thèse, nous nous intéressons à des solutions fortes. De façon générale, nous employons ce terme générique pour désigner des contrôles localement optimaux pour la norme L1. En renforçant la notion d'optimalité locale utilisée, nous nous attendons à obtenir des résultats plus forts. Deux outils sont utilisés de façon essentielle : une technique de relaxation, qui consiste à utiliser plusieurs contrôles simultanément, ainsi qu'un principe de décomposition, qui est un développement de Taylor au second ordre particulier du lagrangien. Les chapitres 2 et 3 portent sur les conditions d'optimalité nécessaires et suffisantes du second ordre pour des solutions fortes de problèmes avec contraintes pures, mixtes et sur l'état final. Dans le chapitre 4, nous réalisons une analyse de sensibilité pour des problèmes relaxés avec des contraintes sur l'état final. Dans le chapitre 5, nous réalisons une analyse de sensibilité pour un problème de production d'énergie nucléaire. Dans la deuxième partie, nous étudions des problèmes de contrôle optimal stochastique sous contrainte en probabilité. Nous étudions une approche par programmation dynamique, dans laquelle le niveau de probabilité est vu comme une variable d'état supplémentaire. Dans ce cadre, nous montrons que la sensibilité de la fonction valeur par rapport au niveau de probabilité est constante le long des trajectoires optimales. Cette analyse nous permet de développer des méthodes numériques pour des problèmes en temps continu. Ces résultats sont présentés dans le chapitre 6, dans lequel nous étudions également une application à la gestion actif-passif<br>This thesis is divided into two parts. In the first part, we study constrained deterministic optimal control problems and sensitivity analysis issues, from the point of view of abstract optimization. Second-order necessary and sufficient optimality conditions, which play an important role in sensitivity analysis, are also investigated. In this thesis, we are interested in strong solutions. We use this generic term for locally optimal controls for the L1-norm, roughly speaking. We use two essential tools: a relaxation technique, which consists in using simultaneously several controls, and a decomposition principle, which is a particular second-order Taylor expansion of the Lagrangian. Chapters 2 and 3 deal with second-order necessary and sufficient optimality conditions for strong solutions of problems with pure, mixed, and final-state constraints. In Chapter 4, we perform a sensitivity analysis for strong solutions of relaxed problems with final-state constraints. In Chapter 5, we perform a sensitivity analysis for a problem of nuclear energy production. In the second part of the thesis, we study stochastic optimal control problems with a probability constraint. We study an approach by dynamic programming, in which the level of probability is a supplementary state variable. In this framework, we show that the sensitivity of the value function with respect to the probability level is constant along optimal trajectories. We use this analysis to design numerical schemes for continuous-time problems. These results are presented in Chapter 6, in which we also study an application to asset-liability management
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Grossman, Mark. "Task Interaction and Control System (TICS) /." Full text open access at:, 1987. http://content.ohsu.edu/u?/etd,140.
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O'Brien, Kevin M. (Kevin Michael). "Task-level control for networked telerobotics." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/39764.
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Arumukhom, Revi Dheepak. "Human Control in a Balancing Task." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1503271214388993.
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Essig, Fiona. "Cognitive control in verbal task switching." Thesis, University of Hertfordshire, 2015. http://hdl.handle.net/2299/16339.
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Task switching produces a number of reliable behavioural measures, the main focus of interest here being 'switch cost', the increase in response time when switching between tasks as opposed to performing them separately. Switch costs are typically measured between two tasks and compared to a single-task repeat condition. Current explanations of switch cost fall broadly into either active reconfiguration based accounts (e.g. Rogers & Monsell, 1995) whereby the extra time taken to switch between tasks is attributable to reconfiguration of task set, or passive carryover accounts (Allport, Styles & Hsieh, 1994) where extra time is accrued by the need to overcome conflict between the current task set and the enduring activity of the previous task set. This thesis used the Continuous Series II (Gurd, 1995), a novel continuous verbal switching task which requires individuals to switch continuously between increasing numbers of overlearned sequences (e.g. days, numbers). The aim was to investigate the application of general (whole-task) switch costs (RT costs), memory-based switching and the differential pattern of errors produced by the task, with a view to determining the most appropriate theoretical model to explain costs in the task. General switch costs are measured over the whole time course of the task from beginning to end, instead of the more usual measurement of switch cost over a single switch or repeat within the whole task. Such long-term measures of switch cost account for 'global representational structures' in the task, which are said to contribute to the cost of switching yet are absent from local transitional measures (Kleinsorge, Heuer & Schmidtke, 2004). Global representational structures account for not only the current and preceding trials actually performed but also the possible alternatives for the preceding, current and subsequent trials, thereby reflecting all representations relating to performance of the tasks. The Continuous Series II (Gurd, 1995) measures costs continuously over time between increasing numbers of verbal tasks and as yet has not been linked to either a reconfiguration or carryover-based account. Initial administration to healthy controls and neurological patients confirmed difficulty-related increasing costs and revealed a dissociation of errors between two versions of the task, one including semantic categories. This suggested differential sources of control overseeing conflict detection and resolution, linked in this work to Kahneman's dual system model (Kahneman, 2011) and suggesting the implication of active control. Further work with monozygotic twins mirrored for handedness revealed no predicted effect of handedness but did reveal the employment of vocalised inner-speech as a successful self cueing device, known to be supportive of active reconfiguration in switching (Monsell, 2005). Such cueing was employed by this sample of older adults but had not appeared to benefit the neurological patients who clearly had reconfiguration deficits. Further development of the two versions of the task also allowed rejection of a passive carryover explanation of switch-cost on the basis that switching to the easier task was not more difficult, counter to the prediction of Allport, Styles & Hsieh (1994). At this stage it was evident that some portion of general cost for the task may be artefactual, as participants displayed behaviour suggesting the order of tasks and their updating nature (task content) may be inflating cost beyond a pure measure of switching (an inevitable risk of general switch cost measurement). Investigation of task order showed that production of the category 'days' appeared to conflate sources of error. Reducing the difficultly of component tasks (removing the need to update items) demonstrated that a substantial proportion of general cost was indeed purely switch-related. Returning to the question of cueing (previously demonstrated to be beneficial when self-generated), the final study introduced explicit external cues, consistently predicted to benefit switching (Monsell, 2005). These cues did not reduce time costs in verbal task switching and furthermore failed to prevent errors of task order. The lack of external cue benefit supports an amended version of the Rogers & Monsell (1995) task-set reconfiguration model as the best explanation of switch costs in verbal task-switching. This amended model relies entirely on internally generated representations in a closed system and supports the role of active control in generating switch-cost. General cost, while incorporating task-related artefacts, rehearsals and error recovery, nevertheless has at its core a switch related element. Furthermore, the failure of cues to extinguish between-task errors negates excessive reliance on working memory and further supports the rejection of passive carryover accounts of task switch cost.
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Aper, Julie A. "Task and ego oriented athletes and zone of optimal function." Virtual Press, 1993. http://liblink.bsu.edu/uhtbin/catkey/879852.
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The purpose of this study is to determine the relationship between task and ego goal orientation and ZOF. The subjects consisted of interscholastic athletes of the men's varsity and junior varsity baseball, men's track and field, and women's track and field teams from a local Midwestern high school. By providing a more concise zone of optimal function (ZOF) by breaking down the zone into three components: psychological, physiological, and competitive (evaluated by the Sport Participation Questionnaire) the athletes may be able to manipulate their ZOF by using the characteristics of their task and ego orientation (evaluated by the TEOSQ). The data was analyzed by doing a series of factor analyses and multiple regressions. After finding four significant factors (two separate psychological, one physiological, one competitive) a multiple regression was employed to determine the relationship between the factors and task and ego orientaXon.Nearly significant was the regression with ego-oriented athletes and the thinking construct which consisted of items 16-18 of the Sport Participation Questionnaire. Also, significant were relationships of the task or ego score and the demographic findings.<br>School of Physical Education
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Carlsson, Jesper. "Optimal Control of Partial Differential Equations in Optimal Design." Doctoral thesis, KTH, Numerisk Analys och Datalogi, NADA, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9293.
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This thesis concerns the approximation of optimally controlled partial differential equations for inverse problems in optimal design. Important examples of such problems are optimal material design and parameter reconstruction. In optimal material design the goal is to construct a material that meets some optimality criterion, e.g. to design a beam, with fixed weight, that is as stiff as possible. Parameter reconstrucion concerns, for example, the problem to find the interior structure of a material from surface displacement measurements resulting from applied external forces. Optimal control problems, particularly for partial differential equations, are often ill-posed and need to be regularized to obtain good approximations. We here use the theory of the corresponding Hamilton-Jacobi-Bellman equations to construct regularizations and derive error estimates for optimal design problems. The constructed Pontryagin method is a simple and general method where the first, analytical, step is to regularize the Hamiltonian. Next its Hamiltonian system is computed efficiently with the Newton method using a sparse Jacobian. An error estimate for the difference between exact and approximate objective functions is derived, depending only on the difference of the Hamiltonian and its finite dimensional regularization along the solution path and its L² projection, i.e. not on the difference of the exact and approximate solutions to the Hamiltonian systems. Another treated issue is the relevance of input data for parameter reconstruction problems, where the goal is to determine a spacially distributed coefficient of a partial differential equation from partial observations of the solution. It is here shown that the choice of input data, that generates the partial observations, affects the reconstruction, and that it is possible to formulate meaningful optimality criteria for the input data that enhances the quality of the reconstructed coefficient. In the thesis we present solutions to various applications in optimal material design and reconstruction.<br>Denna avhandling handlar om approximation av optimalt styrda partiella differentialekvationer för inversa problem inom optimal design. Viktiga exempel på sådana problem är optimal materialdesign och parameterskattning. Inom materialdesign är målet att konstruera ett material som uppfyller vissa optimalitetsvillkor, t.ex. att konstruera en så styv balk som möjligt under en given vikt, medan ett exempel på parameterskattning är att hitta den inre strukturen hos ett material genom att applicera ytkrafter och mäta de resulterande förskjutningarna. Problem inom optimal styrning, speciellt för styrning av partiella differentialekvationer,är ofta illa ställa och måste regulariseras för att kunna lösas numeriskt. Teorin för Hamilton-Jacobi-Bellmans ekvationer används här för att konstruera regulariseringar och ge feluppskattningar till problem inom optimaldesign. Den konstruerade Pontryaginmetoden är en enkel och generell metod där det första analytiska steget är att regularisera Hamiltonianen. I nästa steg löses det Hamiltonska systemet effektivt med Newtons metod och en gles Jacobian. Vi härleder även en feluppskattning för skillnaden mellan den exakta och den approximerade målfunktionen. Denna uppskattning beror endast på skillnaden mellan den sanna och den regulariserade, ändligt dimensionella, Hamiltonianen, båda utvärderade längst lösningsbanan och dessL²-projektion. Felet beror alltså ej på skillnaden mellan den exakta och denapproximativa lösningen till det Hamiltonska systemet. Ett annat fall som behandlas är frågan hur indata ska väljas för parameterskattningsproblem. För sådana problem är målet vanligen att bestämma en rumsligt beroende koefficient till en partiell differentialekvation, givet ofullständiga mätningar av lösningen. Här visas att valet av indata, som genererarde ofullständiga mätningarna, påverkar parameterskattningen, och att det är möjligt att formulera meningsfulla optimalitetsvillkor för indata som ökar kvaliteten på parameterskattningen. I avhandlingen presenteras lösningar för diverse tillämpningar inom optimal materialdesign och parameterskattning.<br>QC 20100712
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Silva, Francisco Jose. "Interior penalty approximation for optimal control problems. Optimality conditions in stochastic optimal control theory." Palaiseau, Ecole polytechnique, 2010. http://pastel.archives-ouvertes.fr/docs/00/54/22/95/PDF/tesisfjsilva.pdf.
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Résumé français : Cette thèse est divisée en deux parties. Dans la première partie on s'intéresse aux problèmes de commande optimale déterministes et on étudie des approximations intérieures pour deux problèmes modèles avec des contraintes de non-négativité sur la commande. Le premier modèle est un problème de commande optimale dont la fonction de coût est quadratique et dont la dynamique est régie par une équation différentielle ordinaire. Pour une classe générale de fonctions de pénalité intérieure, on montre comment calculer le terme principal du développement ponctuel de l'état et de l'état adjoint. Notre argument principal se fonde sur le fait suivant: si la commande optimale pour le problème initial satisfait les conditions de complémentarité stricte pour le Hamiltonien sauf en un nombre fini d'instants, les estimations pour le problème de commande optimale pénalisé peuvent être obtenues à partir des estimations pour un problème stationnaire associé. Nos résultats fournissent plusieurs types de mesures de qualité de l'approximation pour la technique de pénalisation: estimations des erreurs de la commande , estimations des erreurs pour l'état et l'état adjoint et aussi estimations de erreurs pour la fonction valeur. Le second modèle est le problème de commande optimale d'une équation semi-linéaire elliptique avec conditions de Dirichlet homogène au bord, la commande étant distribuée sur le domaine et positive. L'approche est la même que pour le premier modèle, c'est-à-dire que l'on considère une famille de problèmes pénalisés, dont la solution définit une trajectoire centrale qui converge vers la solution du problème initial. De cette manière, on peut étendre les résultats, obtenus dans le cadre d'équations différentielles, au contrôle optimal d'équations elliptiques semi-linéaires. Dans la deuxième partie on s'intéresse aux problèmes de commande optimale stochastiques. Dans un premier temps, on considère un problème linéaire quadratique stochastique avec des contraintes de non-negativité sur la commande et on étend les estimations d'erreur pour l'approximation par pénalisation logarithmique. La preuve s'appuie sur le principe de Pontriaguine stochastique et un argument de dualité. Ensuite, on considère un problème de commande stochastique général avec des contraintes convexes sur la commande. L'approche dite variationnelle nous permet d'obtenir un développement au premier et au second ordre pour l'état et la fonction de coût, autour d'un minimum local. Avec ces développements on peut montrer des conditions générales d'optimalité de premier ordre et, sous une hypothèse géométrique sur l'ensemble des contraintes, des conditions nécessaires du second ordre sont aussi établies<br>Résumé anglais : This thesis is divided in two parts. In the first one we consider deterministic optimal control problems and we study interior approximations for two model problems with non-negativity constraints. The first model is a quadratic optimal control problem governed by a nonautonomous affine ordinary differential equation. We provide a first-order expansion for the penalized state an adjoint state (around the corresponding state and adjoint state of the original problem), for a general class of penalty functions. Our main argument relies on the following fact: if the optimal control satisfies strict complementarity conditions for its Hamiltonian, except for a set of times with null Lebesgue measure, the functional estimates of the penalized optimal control problem can be derived from the estimates of a related finite dimensional problem. Our results provide three types of measure to analyze the penalization technique: error estimates of the control, error estimates of the state and the adjoint state and also error estimates for the value function. The second model we study is the optimal control problem of a semilinear elliptic PDE with a Dirichlet boundary condition, where the control variable is distributed over the domain and is constrained to be non-negative. Following the same approach as in the first model, we consider an associated family of penalized problems, whose solutions define a central path converging to the solution of the original one. In this fashion, we are able to extend the results obtained in the ODE framework to the case of semilinear elliptic PDE constraints. In the second part of the thesis we consider stochastic optimal control problems. We begin withthe study of a stochastic linear quadratic problem with non-negativity control constraints and we extend the error estimates for the approximation by logarithmic penalization. The proof is based is the stochastic Pontryagin's principle and a duality argument. Next, we deal with a general stochastic optimal control problem with convex control constraints. Using the variational approach, we are able to obtain first and second-order expansions for the state and cost function, around a local minimum. This analysis allows us to prove general first order necessary condition and, under a geometrical assumption over the constraint set, second-order necessary conditions are also established
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Amazouz, Achour. "Optimal control for decentralized platooning." Thesis, KTH, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-121541.
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The idea of autonomous vehicles and automated highway systems is no new concept to the automotive industry. The potential benets of such a technology are numerous. The platooning approach would imply energy economy through air drag reduction, but also reduced trac congestion and increased safety. The question of longitudinal control in a platoon conguration is central, the main concern being relative to safety. In this thesis, dierent classical control approaches will be compared and applied to the platooning problem. Among these approaches, one was tested in November 2012 in a demonstration which involved three teams and multiple vehicles from dierent Swedish universities. Constrained optimal control comes with the prospect of increased safety and better handling of some characteristics of physical systems. The main negative impact of this constraint handling lies in its computational complexity. Numerical problems were encountered and described with the use of MPC. Proportional-Integral and Linear Quadratic controllers were retained and applied to the tracking problem in the context of vehicle platooning. These methods will be compared in a simulation environment.
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Carillo-Ureta, Gabriel Eduardo. "Optimal control of fermentation processes." Thesis, City University London, 2003. http://openaccess.city.ac.uk/7584/.
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The general purpose of this thesis is to focus on a particular industrial process (from the beer industry) which serves as a guidance example for optimal control using different algorithms/methods. At the same time, the aim is to demonstrate the capabilities/features of MATLAB and SIMULINK as tools used in programming algorithms and simulation for optimal control of non linear systems. The thesis shows how to approach an optimisation problem with different techniques and to compare them on the same basis. The main reasons for carrying out research on a beer fermentation process can be summarised as follows: this kind of industry represents an up-to-date example of industrial processes in general, the need to compare and evaluate optimisation methods (well established and "modern") on similar circumstances using the sanle process model and finally, give a good foundation for the control engineer to followup this work with different optimisation techniques and/or any other industrial process. The fundamental features of the methods used involve the viability of known previously tested algorithms for optimal control of beer processes with high nonlinearity and constraints; thus testing the flexibility of some of the known MA TLAB Toolboxes for the optimal control of a particular simulated mathematical model. An important aspect of the experimentation that has been carried out, is the creation of a simulated model of a selected beer process by means of including the mathematical equations, parameters and initial conditions into an s-function block. This SIMULINK model also incorporates the particular objective function that can be calculated directly after the simulation of the process for a particular input temperature profile. Together with the use of some available MA TLAB functions for the formulation of particular optimal control techniques, this facilitates the creation of program routines that can be interfaced with the simulated process. The final results using different optimisation methods such as: the gradient method in function space, DIS OPE algorithm, Genetic Algorithms and Sequential Quadratic programming; show substantial improvement in the perfomance index obtained. The optimised temperature profiles found can be implemented for industrial application to provide a maximised ethanol production under particular restrictions, i.e. final byproducts concentration, contamination risk and brisk changes in temperature.
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Sivertsson, Martin. "Optimal Control of Electrified Powertrains." Doctoral thesis, Linköpings universitet, Fordonssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117290.
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Vehicle powertrain electrification, i.e. combining the internal combustion engine (ICE) with an electric motor (EM), is a potential way of meeting the increased demands for efficient and low emission transportation, at a price of increased powertrain complexity since more degrees of freedom (DoF) have been introduced. Optimal control is used in a series of studies of how to best exploit the additional DoFs. In a diesel-electric powertrain the absence of a secondary energy storage and mechanical connection between the ICE and the wheels means that all electricity used by the EMs needs to be produced simultaneously by the ICE, whose rotational speed is a DoF. This in combination with the relatively slow dynamics of the turbocharger in the ICE puts high requirements on good transient control. In optimal control studies, accurate models with good extrapolation properties are needed. For this aim two nonlinear physics based models are developed and made available that fulfill these requirements, these are also smooth in the region of interest, to enable gradient based optimization techniques. Using optimal control and one of the developed models, the turbocharger dynamics are shown to have a strong impact on how to control the powertrain and neglecting these can lead to erroneous estimates both in the response of the powertrain as well as how the powertrain should be controlled. Also the objective, whether time or fuel is to be minimized, influences the engine speed-torque path to be used, even though it is shown that the time optimal solution is almost fuel optimal. To increase the freedom of the powertrain control, a small energy storage can be added to assist in the transients. This is shown to be especially useful to decrease the response time of the powertrain, but the manner it is used, depends on the time horizon of the optimal control problem. The resulting optimal control solutions are for certain cases oscillatory when stationary controls would have been expected. This is shown to be neither an artifact of the discretization used nor a result of the modeling assumptions used. Instead it is for the formulated problems actually optimal to use periodic control in certain stationary operating points. Measurements show that the pumping torque is different depending on whether the controls are periodic or constant despite the same average value. Whether this is beneficial or not depends on the operating point and control frequency, but can be predicted using optimal periodic control theory. In hybrid electric vehicles (HEV) the size of the energy storage reduces the impact of poor transient control, since the battery can compensate for the slower dynamics of the ICE. For HEVs the problem instead is how and when to use the battery to ensure good fuel economy. An adaptive map-based equivalent consumption minimization strategy controller using battery state of charge for feedback control is designed and tested in a real vehicle with good results, even when the controller is started with poor initial values. In a plug-in HEV (PHEV) the battery is even larger, enabling all-electric drive, making it it desirable to use the energy in the battery during the driving mission. A controller is designed and implemented for a PHEV Benchmark and is shown to perform well even for unknown driving cycles, requiring a minimum of future knowledge.<br>Elektrifiering av drivlinan i fordon är ett sätt att möta kraven på transporter med hög effektivitet och låga utsläpp. Att byta ut förbränningsmotorn mot en elmotor kan ge vinningar avseende effektivitet, prestanda och utsläpp, men till en kostnad av lägre mobilitet på grund av eletriska energilagers relativt låga energitäthet i jämförelse med fossila bränslen. Att istället komplettera förbränningsmotorn med en elmotor erbjuder möjligheten att kombinera de två systemens fördelar och samtidigt undvika nackdelarna. Att använda mer än en motor i drivlinan ökar komplexiteten eftersom fler frihetsgrader har introducerats. Detta ställer ökade krav på utformningen av reglersystemet för att få ut det mesta av potentialen i drivlinan. I optimal styrning använder man matematiska modeller och optimeringsalgoritmer för att beräkna hur man bäst styr det modellerade systemet. Storleken på det elektriska energilagret påverkar dock valet av optimal styrnings-metod samt vilken detaljnivå på modellerna som behövs. I avhandlingen används optimal styrning i en serie studier av hur man bäst utnyttjar de extra frihetsgraderna som elektrifieringen har introducerat. I en diesel-elektrisk drivlina finns det ingen mekanisk koppling mellan motorn och hjulen, likt en växellåda i ett vanligt fordon, vilket gör att dieselmotorns varvtal är en frihetsgrad som måste styras. Avsaknaden av elektriskt energilager leder också till att all elektrisk energi till elmotorn måste produceras av förbränningsmotorn exakt då den behövs. Dessa två egenskaper, i kombination med den långsamma dynamiken hos turboaggregatet, ställer detta höga krav på god transientreglering. För att studera optimal styrning krävs bra modeller med goda extrapoleringsegenskaper. Med avseende på detta utvecklas två fysik-baserade modeller som uppfyller dessa krav och dessutom är tillräckligt glatta i det relevanta arbetsområdet för att möjliggöra gradient-baserade optimeringstekniker. Med optimal styrning och en av de utvecklade modellerna visas turbons dynamik ha stor påverkan på hur drivlinan bör styras. Att försumma turbodynamiken kan leda till felaktiga uppskattningar, både av drivlinans responstid, men även hur den bör styras. Kriteriet, det vill säga om bränsle eller tidsåtgången minimeras, påverkar också vilken motorvarvtal-motormoment-väg som är optimal, även om det visas att den tidsoptimala lösningen är nästan bränsleoptimal. För att ytterligare öka frihetsgraden i drivlinan kan ett elektriskt energilager användas för att assistera i transienterna. Detta visar sig vara särskilt användbart för att minska responstiden hos drivlinan, men hur det ska använda beror på tidshorisonten på optimeringsproblemet De resulterande optimala styrsignalerna är i vissa fall oscillerande där konstanta styrsignaler förväntas. Detta visas vara vare sig en effekt av den använda diskretiseringen eller modelleringsvalen som är gjorda. Istället är det för de lösta problemen faktiskt optimalt att använda periodiska styrsignaler för vissa stationära arbetspunkter. I experiment visas att pumparbetet skiljer sig beroende på om periodiska eller konstanta styrsignaler används, även om medelvärdet är detsamma. Huruvida detta ökar effektiviteten eller inte beror på arbetspunkt och periodtid. För hybridelektriska fordon (HEV) så minskar batteriets storlek effekten av dålig transientreglering då batteriet kan användas för att kompensera för den långsamma förbränningsmotordynamiken. Istället blir problemet i huvudsak hur mycket och när batteriet ska användas för att få god bränsleekonomi. En adaptiv mapp-baserad ekvivalentförbruknings-minimerande styrlag (ECMS) med återkopplad reglering baserad på batteriets laddningsnivå, utvecklas och testas i riktigt fordon med gott resultat, även vid dålig initialisering av regulatorn. För plug-in hybrider (PHEV) är batteriet större och kan dessutom laddas från elnätet, vilket medför möjlighet till rent elektrisk drift och att det är önskvärt att använda energin i batteriet under köruppdraget. För att minska energiåtgången är det däremot ofta lönsamt att blanda energin från bränsle och batteriet kontinuerligt under köruppdraget och se till att batteriet töms lagom till slutet av köruppdraget. För att åstadkomma detta måste då även urladdningstakten bestämmas. En regulator utvecklas för att minimera energiåtgången för en PHEV, det vill säga som försöker använda lagom av batteriet så det ska räcka hela vägen, men inte längre. Denna regulator implementeras för ett referensproblem, med gott resultat även för okända körcykler, trots ett minimum av framtidskunskap.
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Ruggiu, Jean-Marc. "Optimal control for adaptive optics." Thesis, University of Kent, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.342157.
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Ming, Ju. "Optimal control of stochastic flow." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3369866.
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Palladino, Michele. "Optimal control of differential inclusions." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/25271.
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The thesis concerns some recent advances on necessary conditions for optimal control problems, paying particular attention to the case in which the velocity constraint is expressed in terms of a multifunction. In the first part of the thesis we have explored the link which arises between relaxation and first order necessary conditions. Relaxation is a widely used regularization procedure in optimal control, involving the replacement of velocity sets by their convex hulls, to ensure the existence of a minimizer. It turns out that some pathological situations arise in which the costs of relaxed and original problems do not coincide (infimum gap conditions). In this case, we cannot obtain approximate solution of the optimal control problem of interest. In particular, we show how necessary conditions expressed in terms of Fully Convexified Hamiltonian Inclusion are a↵ected by the presence of an infimum gap. Applications of these results are showed also in the case in which the velocity constraint is expressed in terms of controlled di↵erential equations. In the second part of the thesis we study the regularity of the Hamiltonian along the optimal trajectory for problems with state constraint. Two applications of these properties are demonstrated. One is to derive improved conditions which guarantee the nondegeneracy of necessary conditions of optimality, in the form of a Hamiltonian inclusion. The other application is to derive new, less restrictive, conditions under which minimizers in the calculus of variations have bounded slope.
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Sinha, Abhishek Ph D. Massachusetts Institute of Technology. "Optimal control for wireless networks." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113740.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 223-231).<br>One of the most fundamental problems in Computer Networking is to efficiently route packets belonging to different sessions, such as unicast, broadcast, multicast and anycast, collectively known as the generalized flows. The goal of this thesis is to design an efficient routing, and wireless link scheduling policy, that maximizes net throughput. Currently, the only known throughput-optimal policy is the Backpressure policy for the unicast problem. In this thesis, we propose provably optimal algorithms for the broadcast and the generalized flow problems. Our study begins with the problem of optimal broadcasting in a wireless Directed Acyclic Graph (DAG). Existing policies achieve the broadcast capacity by balancing traffic over a set of spanning trees, which are difficult to maintain in a large and time-varying network. We propose a fundamentally new broadcast policy, which is decentralized, utilizes local information only, does not require the use of global topological structures, such as spanning trees. It also yields a new and computationally efficient characterization of the broadcast capacity in wireless DAGs. We next study the problem of broadcasting in networks with arbitrary topology and derive a new dynamic broadcast policy which can be viewed as "Backpressure on sets". This yields an efficient solution to the problem when combined with a multi-class in-order packet scheduling rule. Finally, we study the generalized flow problem and derive an online dynamic policy, called Universal Max-Weight (UMW). To the best of our knowledge, UMW is the first throughput-optimal algorithm of such versatility in this context. Conceptually, the UMW policy is derived by relaxing the precedence constraints associated with multi-hop routing and then solving a min-cost routing and max-weight scheduling problem on a virtual network of queues. When specialized to the unicast setting, unlike Backpressure, the UMW policy yields a throughput-optimal cycle-free routing and link scheduling policy. The proposed algorithmic paradigm is surprisingly general and can be used to solve other related problems, such as optimal broadcasting in wireless networks with point-to-multipoint links. The proof of throughput-optimality of the UMW policy combines techniques from stochastic Lyapunov theory with a sample path argument from adversarial queueing theory and may be of independent theoretical interest.<br>by Abhishek Sinha.<br>Ph. D.
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Bonnet, Benoît. "Optimal control in Wasserstein spaces." Electronic Thesis or Diss., Aix-Marseille, 2019. http://www.theses.fr/2019AIXM0442.
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Une vaste quantité d'outils mathématiques permettant la modélisation et l'analyse des problèmes multi-agents ont récemment été développés dans le cadre de la théorie du transport optimal. Dans cette thèse, nous étendons pour la première fois plusieurs de ces concepts à des problématiques issues de la théorie du contrôle. Nous démontrons plusieurs résultats sur ce sujet, notamment des conditions nécessaires d'optimalité de type Pontryagin dans les espaces de Wasserstein, des conditions assurant la régularité intrinsèque de solutions optimales, des conditions suffisantes pour l'émergence de différents motifs, ainsi qu'un résultat auxiliaire à propos des arrangements de certaines singularités en géométrie sous-Riemannienne<br>A wealth of mathematical tools allowing to model and analyse multi-agent systems has been brought forth as a consequence of recent developments in optimal transport theory. In this thesis, we extend for the first time several of these concepts to the framework of control theory. We prove several results on this topic, including Pontryagin optimality necessary conditions in Wasserstein spaces, intrinsic regularity properties of optimal solutions, sufficient conditions for different kinds of pattern formation, and an auxiliary result pertaining to singularity arrangements in Sub-Riemannian geometry
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Maslovskaya, Sofya. "Inverse Optimal Control : theoretical study." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLY013/document.
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Cette thèse s'insère dans un projet plus vaste, dont le but est de s'attaquer aux fondements mathématiques du problème inverse en contrôle optimal afin de dégager une méthodologie générale utilisable en neurophysiologie. Les deux questions essentielles sont : (a) l'unicité d'un coût pour une synthèse optimale donnée (injectivité); (b) la reconstruction du coût à partir de la synthèse. Pour des classes de coût générales, le problème apparaît très difficile même avec une dynamique triviale. On a donc attaqué l'injectivité pour des classes de problèmes spéciales : avec un coût quadratique, la dynamique étant soit non-holonome, soit affine en le contrôle. Les résultats obtenus ont permis de traiter la reconstruction pour le problème linéaire-quadratique<br>This PhD thesis is part of a larger project, whose aim is to address the mathematical foundations of the inverse problem in optimal control in order to reach a general methodology usable in neurophysiology. The two key questions are : (a) the uniqueness of a cost for a given optimal synthesis (injectivity) ; (b) the reconstruction of the cost from the synthesis. For general classes of costs, the problem seems very difficult even with a trivial dynamics. Therefore, the injectivity question was treated for special classes of problems, namely, the problems with quadratic cost and a dynamics, which is either non-holonomic (sub-Riemannian geometry) or control-affine. Based on the obtained results, we propose a reconstruction algorithm for the linear-quadratic problem
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Teerikoski, Sakari. "Optimal control of clarifier-thickeners." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-319980.
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A computer model for a general clarifier-thickener has been made and used for comparing different strategies for control of such dewatering units through simulations. The model builds on widely acknowledged theory for modelling clarifier-thickeners - discretizing the settling PDE into a set of ODEs so that concentrations of solids at discrete depths inside the unit become the states of the numerical model - and it was written in the Modelica language using the modelling and simulation environment Dymola. The work of estimating model parameters for themodel and comparing different control strategies was made looking at one particular clarifier-thickener at the company Boliden's mineral processing plant in Garpenberg. Among the control strategies that were compared in simulations were simple PID control and cascade control as well as more advanced control schemes. The simulations showed that the optimal control strategy to use is cascade control using rake torque as a secondary variable, which makes sense in particular for large thickeners such as the one mainly considered in this work.
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Hazell, Andrew. "Discrete-time optimal preview control." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/8472.
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There are many situations in which one can preview future reference signals, or future disturbances. Optimal Preview Control is concerned with designing controllers which use this preview to improve closed-loop performance. In this thesis a general preview control problem is presented which includes previewable disturbances, dynamic weighting functions, output feedback and nonpreviewable disturbances. It is then shown how a variety of problems may be cast as special cases of this general problem; of particular interest is the robust preview tracking problem and the problem of disturbance rejection with uncertainty in the previewed signal. The general preview problem is solved in both the Fh and Beo settings. The H2 solution is a relatively straightforward extension ofpreviously known results, however, our contribution is to provide a single framework that may be used as a reference work when tackling a variety of preview problems. We also provide some new analysis concerning the maximum possible reduction in closed-loop H2 norm which accrues from the addition of preview action. The solution to the Hoo problem involves a completely new approach to Hoo preview control, in which the structure of the associated Riccati equation is exploited in order to find an efficient algorithm for computing the optimal controller. The problem tackled here is also more generic than those previously appearing in the literature. The above theory finds obvious applications in the design of controllers for autonomous vehicles, however, a particular class of nonlinearities found in typical vehicle models presents additional problems. The final chapters are concerned with a generic framework for implementing vehicle preview controllers, and also a'case study on preview control of a bicycle.
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Minami, Yuki. "Optimal Dynamic Quantizers for Control." 京都大学 (Kyoto University), 2009. http://hdl.handle.net/2433/123855.
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Couchman, Ian Jesse. "Optimal control of fluid mixing." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520860.
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Bell, Margaret. "Robust optimal receding horizon control." Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/7348.
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Receding horizon optimal control has a long history and provides the basis for several of the currently popular techniques for model predictive control of chemical processes. Based on a prediction of the current state of the process, derived from plant measurements, and predictions of the likely input conditions over a certain period ahead (the time horizon), optimal controls are computed to maximise a given "performance function", which can be either an economic or technical measure of performance. The state predictions are regularly updated as new measurements are made and the controls are re-computed if either the current state or the predicted input conditions change significantly. An important advantage of computing optimal controls is that this can take direct account of process operating constraints. However, general inequality constraints have always posed a difficult problem in numerical optimal control algorithms and we propose a new algorithm for dealing with this problem for systems described by DAEs of any index. Due to both the excessive time required for model development and the excessive computational time required for a full model, the on-line model is generally of a much lower complexity than the true system and although parameters in the model may be re-estimated using plant measurements, there is inevitably some uncertainty in the model predictions as well as in the input predictions. The controls must therefore be robust, giving reasonable performance in the face of variations of actual conditions from the predictions. To obtain a sufficiently simple controller, the H∞ approach has been to design a controller to perform optimally if the worst possible set of inputs and model predictions actually occur, and this can also be applied within the receding horizon optimal control framework. The result is a game, with the controls playing against the uncertain inputs and model parameters. However, this does not guarantee robustness in the presence of inequality constraints and here we propose a new simple technique for dealing with this problem, which exploits the sampling interval of the receding horizon formulation of the problem.
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Perantoni, Giacomo. "Optimal control of vehicle systems." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:b75fa69c-ebe0-4812-98e9-984d93476d37.
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This thesis studies the optimal control of vehicular systems, focusing on the solution of minimum-lap-time problems for a Formula 1 car. The basic optimal control theory is summarised as an infinite-dimensional extension of optimisation theory. The relevant numerical techniques for optimisation and integral approximation are compared in view of the application to vehicle systems. The classical brachistochrone problem is revisited from an optimal control perspective, with two vehicle-relevant generalisations. Closed-form solutions are derived for both the optimal trajectory and transit time. Problems involving a steerable disc rolling on the interior surface of a hemisphere are studied. For three-dimensional problems of this type, which involve rolling bodies and nonholonomic constraints, numerical solutions are used. The identification of 3D race track models from measured GPS data is treated as a problem in the differential geometry of curves and surfaces. Curvilinear coordinates are adopted to facilitate optimal control solutions. The track is specified in terms of three displacement-dependent curvatures and two edge variables. The differential model is smoothed using numerical optimal control techniques. The Barcelona track is considered as an illustrative example. The minimum-lap-time problem for a Formula 1 car on a flat track is solved using direct transcription. The driven line and multiple car setup parameters are optimised simultaneously. It is shown that significant lap-time reductions can be obtained from track-specific setup parameter optimisation. Reduced computing times are achieved using a combination of analytical derivatives, model non-dimensionalisation and problem scaling. The optimal control of the car on a 3D track is studied; the results are compared with flat-track solutions. Contemporary kinetic energy-recovery systems are studied and compared with future hybrid kinetic-thermal energy-recovery systems. It is demonstrated that these systems can produce contemporary lap time using approximately two-thirds of the fuel required by present-day vehicles.