Log in

Relevant bibliographies by topics / The task of optimal control / Journal articles

To see the other types of publications on this topic, follow the link: The task of optimal control.

Journal articles on the topic 'The task of optimal control'

Author: Grafiati

Published: 4 May 2022

Last updated: 5 May 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'The task of optimal control.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

KOITABASHI, Tatsuo, and Hikaru INOOKA. "Control behavior of human operator in an optimal control task." Japanese journal of ergonomics 23, no. 5 (1987): 317–24. http://dx.doi.org/10.5100/jje.23.317.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Yao, Yuhua, and Jitao Sun. "Optimal control of multi-task Boolean control networks via temporal logic." Systems & Control Letters 156 (October 2021): 105007. http://dx.doi.org/10.1016/j.sysconle.2021.105007.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Mistry, Michael, Evangelos Theodorou, Stefan Schaal, and Mitsuo Kawato. "Optimal control of reaching includes kinematic constraints." Journal of Neurophysiology 110, no. 1 (2013): 1–11. http://dx.doi.org/10.1152/jn.00794.2011.

Full text

Abstract:

We investigate adaptation under a reaching task with an acceleration-based force field perturbation designed to alter the nominal straight hand trajectory in a potentially benign manner: pushing the hand off course in one direction before subsequently restoring towards the target. In this particular task, an explicit strategy to reduce motor effort requires a distinct deviation from the nominal rectilinear hand trajectory. Rather, our results display a clear directional preference during learning, as subjects adapted perturbed curved trajectories towards their initial baselines. We model this behavior using the framework of stochastic optimal control theory and an objective function that trades off the discordant requirements of 1) target accuracy, 2) motor effort, and 3) kinematic invariance. Our work addresses the underlying objective of a reaching movement, and we suggest that robustness, particularly against internal model uncertainly, is as essential to the reaching task as terminal accuracy and energy efficiency.

APA, Harvard, Vancouver, ISO, and other styles

4

Gong, Yanmin, Lingbo Wei, Yuanxiong Guo, Chi Zhang, and Yuguang Fang. "Optimal Task Recommendation for Mobile Crowdsourcing With Privacy Control." IEEE Internet of Things Journal 3, no. 5 (2016): 745–56. http://dx.doi.org/10.1109/jiot.2015.2512282.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Pepelyaeva, T. V., L. B. Vovk, and I. Yu Demchenko. "Optimal Strategies for the Multi-Task Inventory Control Model." Cybernetics and Systems Analysis 52, no. 1 (2016): 107–12. http://dx.doi.org/10.1007/s10559-016-9805-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Lee, Jaemin, Efstathios Bakolas, and Luis Sentis. "Hierarchical Task-Space Optimal Covariance Control With Chance Constraints." IEEE Control Systems Letters 6 (2022): 2359–64. http://dx.doi.org/10.1109/lcsys.2022.3153094.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Galicki, M. "Kinematically Optimal Robust Control of Redundant Manipulators." International Journal of Applied Mechanics and Engineering 22, no. 4 (2017): 839–65. http://dx.doi.org/10.1515/ijame-2017-0055.

Full text

Abstract:

Abstract This work deals with the problem of the robust optimal task space trajectory tracking subject to finite-time convergence. Kinematic and dynamic equations of a redundant manipulator are assumed to be uncertain. Moreover, globally unbounded disturbances are allowed to act on the manipulator when tracking the trajectory by the endeffector. Furthermore, the movement is to be accomplished in such a way as to minimize both the manipulator torques and their oscillations thus eliminating the potential robot vibrations. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we derive a class of chattering-free robust kinematically optimal controllers, based on the estimation of transpose Jacobian, which seem to be effective in counteracting both uncertain kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a redundant manipulator of a SCARA type consisting of the three revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers as well as comparisons with other well known control schemes.

APA, Harvard, Vancouver, ISO, and other styles

8

Lewis, Debra. "Modeling student engagement using optimal control theory." Journal of Geometric Mechanics 14, no. 1 (2022): 131. http://dx.doi.org/10.3934/jgm.2021032.

Full text

Abstract:

<p style='text-indent:20px;'>Student engagement in learning a prescribed body of knowledge can be modeled using optimal control theory, with a scalar state variable representing mastery, or self-perceived mastery, of the material and control representing the instantaneous cognitive effort devoted to the learning task. The relevant costs include emotional and external penalties for incomplete mastery, reduced availability of cognitive resources for other activities, and psychological stresses related to engagement with the learning task. Application of Pontryagin's maximum principle to some simple models of engagement yields solutions of the synthesis problem mimicking familiar behaviors including avoidance, procrastination, and increasing commitment in response to increasing mastery.</p>

APA, Harvard, Vancouver, ISO, and other styles

9

Gu, Edward Y. L., and Naim A. Kheir. "Optimal task planning and control of multi-robot coordinated workcells." IFAC Proceedings Volumes 32, no. 2 (1999): 671–76. http://dx.doi.org/10.1016/s1474-6670(17)56114-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Diedrichsen, Jörn. "Optimal Task-Dependent Changes of Bimanual Feedback Control and Adaptation." Current Biology 17, no. 19 (2007): 1675–79. http://dx.doi.org/10.1016/j.cub.2007.08.051.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Lin, Jianping, Nikhil V. Divekar, Ge Lv, and Robert D. Gregg. "Optimal Task-Invariant Energetic Control for a Knee-Ankle Exoskeleton." IEEE Control Systems Letters 5, no. 5 (2021): 1711–16. http://dx.doi.org/10.1109/lcsys.2020.3043838.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Ruff, Heath, Gloria Calhoun, Elizabeth Frost, Kyle Behymer, and Jessica Bartik. "Comparison of Adaptive, Adaptable, and Hybrid Automation for Surveillance Task Completion in a Multi-Task Environment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 155–59. http://dx.doi.org/10.1177/1541931218621036.

Full text

Abstract:

Increasing applications of automation in system designs raise issues on how to achieve an ideal balance of automation with human interaction for optimal operator situation awareness and performance. This experiment examined four automation control schemes applied to surveillance tasks performed in a multi-task simulation environment. Participants completed trials with four level of automation (LOA) control schemes: fixed, performance-based adaptive, adaptable (participant controls LOA), and hybrid (adaptive and adaptable). Results showed that task accuracy was better when participants controlled LOA. Participants also preferred adaptable automation.

APA, Harvard, Vancouver, ISO, and other styles

13

Jasinska, Dorota, and Leszek Mikulski. "Strength optimization of structural elements by means of optimal control." MATEC Web of Conferences 262 (2019): 10006. http://dx.doi.org/10.1051/matecconf/201926210006.

Full text

Abstract:

This paper investigates the optimal shaping of the web height of an I-section steel portal frame. The problem is formulated as a control theory task. From a mathematical perspective, the task involves solving the multipoint boundary value problem for the system of forty-three differential equations. The solution is compared to results obtained from the finite element software Abaqus.

APA, Harvard, Vancouver, ISO, and other styles

14

Bachmann, Freya, Gilbert Koch, Marc Pfister, Gabor Szinnai, and Johannes Schropp. "OptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control." Journal of Optimization Theory and Applications 189, no. 1 (2021): 46–65. http://dx.doi.org/10.1007/s10957-021-01819-w.

Full text

Abstract:

AbstractProviding the optimal dosing strategy of a drug for an individual patient is an important task in pharmaceutical sciences and daily clinical application. We developed and validated an optimal dosing algorithm (OptiDose) that computes the optimal individualized dosing regimen for pharmacokinetic–pharmacodynamic models in substantially different scenarios with various routes of administration by solving an optimal control problem. The aim is to compute a control that brings the underlying system as closely as possible to a desired reference function by minimizing a cost functional. In pharmacokinetic–pharmacodynamic modeling, the controls are the administered doses and the reference function can be the disease progression. Drug administration at certain time points provides a finite number of discrete controls, the drug doses, determining the drug concentration and its effect on the disease progression. Consequently, rewriting the cost functional gives a finite-dimensional optimal control problem depending only on the doses. Adjoint techniques allow to compute the gradient of the cost functional efficiently. This admits to solve the optimal control problem with robust algorithms such as quasi-Newton methods from finite-dimensional optimization. OptiDose is applied to three relevant but substantially different pharmacokinetic–pharmacodynamic examples.

APA, Harvard, Vancouver, ISO, and other styles

15

Andre, Anthony D., and Patricia A. Cashion. "Tracking Hesitations as a Function of Task/Control Integration." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39, no. 21 (1995): 1370–74. http://dx.doi.org/10.1177/154193129503902103.

Full text

Abstract:

This study examines the issue of compatibility between task requirements (integrated vs. independent) and control configurations (integrated vs. separated) in the context of a dual-task environment. In the two experiments reported here, subjects were required to time-share a continuous tracking task with a discrete response task. The results showed a greater number of tracking hesitations when these tasks were mapped to separate controls than when they were mapped to the same control, regardless of the level of task integration employed here. We conclude that integrated controls produce less hesitations for time-shared integrated tasks and displays, but can not make conclusions concerning the optimal control configuration for time-shared independent tasks. The results also highlight the multi-dimensional nature of the concept of task integration and suggest that display and temporal dimensions of the concept might outweigh the response dimension.

APA, Harvard, Vancouver, ISO, and other styles

16

Il’ina, Natalya A. "Two-channel time-optimal control of nonstationary heat conductive process with account for response time of boundary control actions." Vestnik of Samara State Technical University. Technical Sciences Series 29, no. 2 (2021): 47–60. http://dx.doi.org/10.14498/tech.2021.2.3.

Full text

Abstract:

The task of organization a closed time-optimal control system of linear object with distributed parameters of parabolic type is considered. The object has two lumped internal controls for the power of heat sources excited in the electromagnetic field of an inductor. The proposed method for the synthesis of optimal controllers uses an alternance method for calculating the optimal program controls for each of the control actions. An example of the construction of a quasi-optimal time control system for the process of periodic induction heating of a metal workpiece with constant values of the feedback coefficients calculated for the most characteristic initial spatial distribution is given.

APA, Harvard, Vancouver, ISO, and other styles

17

Mancuso, Giulio, Enrico Bini, and Gabriele Pannocchia. "Optimal Computational Resource Allocation for Control Task under Fixed Priority Scheduling." IFAC Proceedings Volumes 44, no. 1 (2011): 12599–604. http://dx.doi.org/10.3182/20110828-6-it-1002.01545.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Kulczycki, Piotr. "A Random Approach to Time-Optimal Control." Journal of Dynamic Systems, Measurement, and Control 121, no. 3 (1999): 542–43. http://dx.doi.org/10.1115/1.2802509.

Full text

Abstract:

This paper concerns the time-optimal control for objects described by a random differential inclusion with discontinous right-hand side, representing the second law of Newtonian mechanics and taking into account a complex model of resistance to motion. Such a task has broad technical applications, especially in robotics. By generalizing the concept of the classic switching curve to the switching region, it is possible to construct in practice a range of convenient suboptimal control structures that provide many advantages, especially in respect to robustness.

APA, Harvard, Vancouver, ISO, and other styles

19

Lee, Jeong Yoon, Youngmin Oh, Sung Shin Kim, Robert A. Scheidt, and Nicolas Schweighofer. "Optimal Schedules in Multitask Motor Learning." Neural Computation 28, no. 4 (2016): 667–85. http://dx.doi.org/10.1162/neco_a_00823.

Full text

Abstract:

Although scheduling multiple tasks in motor learning to maximize long-term retention of performance is of great practical importance in sports training and motor rehabilitation after brain injury, it is unclear how to do so. We propose here a novel theoretical approach that uses optimal control theory and computational models of motor adaptation to determine schedules that maximize long-term retention predictively. Using Pontryagin’s maximum principle, we derived a control law that determines the trial-by-trial task choice that maximizes overall delayed retention for all tasks, as predicted by the state-space model. Simulations of a single session of adaptation with two tasks show that when task interference is high, there exists a threshold in relative task difficulty below which the alternating schedule is optimal. Only for large differences in task difficulties do optimal schedules assign more trials to the harder task. However, over the parameter range tested, alternating schedules yield long-term retention performance that is only slightly inferior to performance given by the true optimal schedules. Our results thus predict that in a large number of learning situations wherein tasks interfere, intermixing tasks with an equal number of trials is an effective strategy in enhancing long-term retention.

APA, Harvard, Vancouver, ISO, and other styles

20

Al-Gallaf, E. A. "Multi-fingered robot hand optimal task force distribution." Robotics and Autonomous Systems 54, no. 1 (2006): 34–51. http://dx.doi.org/10.1016/j.robot.2005.09.016.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Achille, Alessandro, and Stefano Soatto. "A Separation Principle for Control in the Age of Deep Learning." Annual Review of Control, Robotics, and Autonomous Systems 1, no. 1 (2018): 287–307. http://dx.doi.org/10.1146/annurev-control-060117-105140.

Full text

Abstract:

We review the problem of defining and inferring a state for a control system based on complex, high-dimensional, highly uncertain measurement streams, such as videos. Such a state, or representation, should contain all and only the information needed for control and discount nuisance variability in the data. It should also have finite complexity, ideally modulated depending on available resources. This representation is what we want to store in memory in lieu of the data, as it separates the control task from the measurement process. For the trivial case with no dynamics, a representation can be inferred by minimizing the information bottleneck Lagrangian in a function class realized by deep neural networks. The resulting representation has much higher dimension than the data (already in the millions) but is smaller in the sense of information content, retaining only what is needed for the task. This process also yields representations that are invariant to nuisance factors and have maximally independent components. We extend these ideas to the dynamic case, where the representation is the posterior density of the task variable given the measurements up to the current time, which is in general much simpler than the prediction density maintained by the classical Bayesian filter. Again, this can be finitely parameterized using a deep neural network, and some applications are already beginning to emerge. No explicit assumption of Markovianity is needed; instead, complexity trades off approximation of an optimal representation, including the degree of Markovianity.

APA, Harvard, Vancouver, ISO, and other styles

22

Glocker, Markus, Christian Reinl, and Oskar von Stryk. "OPTIMAL TASK ALLOCATION AND DYNAMIC TRAJECTORY PLANNING FOR MULTI-VEHICLE SYSTEMS USING NONLINEAR HYBRID OPTIMAL CONTROL." IFAC Proceedings Volumes 39, no. 20 (2006): 38–43. http://dx.doi.org/10.3182/20061002-2-br-4906.00008.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Fujimoto, Hideo, Liu-Cun Zhu, and Karim Abdel-Malek. "Image-based Visual Servoing for Optimal Grasping." Journal of Robotics and Mechatronics 13, no. 5 (2001): 479–87. http://dx.doi.org/10.20965/jrm.2001.p0479.

Full text

Abstract:

One of the most common tasks in robotics is grasping. Although the formulation of optimal grasping has been addressed using a variety of approaches, there are only a few grasping systems that can operate in uncertain dynamic environments. In this paper, we present an image-based visual servoing method and system for optimal object grasping by introducing the method of visual vectors. A CCD camera mounted on a robot end-effector constructs the visually guided servo control system and the control scheme lends itself to task-level specification of manipulation goals. The proposed approach integrates vision, grasp planning, and vision=guided control to accomplish the optimal grasping task. The grasping task is to control the robot so the vectors of the end-effector's landmark (e.g., finger vector) and a target object's grasp coincide. These vectors can be used to perform the work of a stable grasping of an object that is presented in an unstructured manner. Visual vectors in image frame are obtained by analyzing the object's image and projection. Our objective in implementing vector processing is to estimate the vector error between the finger and grasp vectors, and to control the robot to eliminate kinematic errors. The proposed model is illustrated through examples and its effectiveness is validated using computer simulation.

APA, Harvard, Vancouver, ISO, and other styles

24

Córdova Bulens, David, Frédéric Crevecoeur, Jean-Louis Thonnard, and Philippe Lefèvre. "Optimal use of limb mechanics distributes control during bimanual tasks." Journal of Neurophysiology 119, no. 3 (2018): 921–32. http://dx.doi.org/10.1152/jn.00371.2017.

Full text

Abstract:

Bimanual tasks involve the coordination of both arms, which often offers redundancy in the ways a task can be completed. The distribution of control across limbs is often considered from the perspective of handedness. In this context, although there are differences across dominant and nondominant arms during reaching control ( Sainburg 2002 ), previous studies have shown that the brain tends to favor the dominant arm when performing bimanual tasks ( Salimpour and Shadmehr 2014 ). However, biomechanical factors known to influence planning and control in unimanual tasks may also generate limb asymmetries in force generation, but their influence on bimanual control has remained unexplored. We investigated this issue in a series of experiments in which participants were instructed to generate a 20-N force with both arms, with or without perturbation of the target force during the trial. We modeled the task in the framework of optimal feedback control of a two-link model with six human-like muscles groups. The biomechanical model predicted a differential contribution of each arm dependent on the orientation of the target force and joint configuration that was quantitatively matched by the participants’ behavior, regardless of handedness. Responses to visual perturbations were strongly influenced by the perturbation direction, such that online corrections also reflected an optimal use of limb biomechanics. These results show that the nervous system takes biomechanical constraints into account when optimizing the distribution of forces generated across limbs during both movement planning and feedback control of a bimanual task. NEW & NOTEWORTHY Here, we studied a bimanual force production task to examine the effects of biomechanical constraints on the distribution of control across limbs. Our findings show that the central nervous system optimizes the distribution of force across the two arms according to the joint configuration of the upper limbs. We further show that the underlying mechanisms influence both movement planning and online corrective responses to sudden changes in the target force.

APA, Harvard, Vancouver, ISO, and other styles

25

Yang, Tong, Jaime Valls Miro, Yue Wang, and Rong Xiong. "Optimal Task-Space Tracking With Minimum Manipulator Reconfiguration." IEEE Robotics and Automation Letters 7, no. 2 (2022): 5079–86. http://dx.doi.org/10.1109/lra.2022.3153725.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Ronsse, Renaud, Kunlin Wei, and Dagmar Sternad. "Optimal Control of a Hybrid Rhythmic-Discrete Task: The Bouncing Ball Revisited." Journal of Neurophysiology 103, no. 5 (2010): 2482–93. http://dx.doi.org/10.1152/jn.00600.2009.

Full text

Abstract:

Rhythmically bouncing a ball with a racket is a hybrid task that combines continuous rhythmic actuation of the racket with the control of discrete impact events between racket and ball. This study presents experimental data and a two-layered modeling framework that explicitly addresses the hybrid nature of control: a first discrete layer calculates the state to reach at impact and the second continuous layer smoothly drives the racket to this desired state, based on optimality principles. The testbed for this hybrid model is task performance at a range of increasingly slower tempos. When slowing the rhythm of the bouncing actions, the continuous cycles become separated into a sequence of discrete movements interspersed by dwell times and directed to achieve the desired impact. Analyses of human performance show increasing variability of performance measures with slower tempi, associated with a change in racket trajectories from approximately sinusoidal to less symmetrical velocity profiles. Matching results of model simulations give support to a hybrid control model based on optimality, and therefore suggest that optimality principles are applicable to the sensorimotor control of complex movements such as ball bouncing.

APA, Harvard, Vancouver, ISO, and other styles

27

Ledkov, Alexander Alexander. "OPTIMAL CONTROL OF A TETHER DEPLOYMENT IN THE TASK OF PAYLOAD DEORBITING." V mire nauchnykh otkrytiy, no. 6.1 (November 22, 2014): 559. http://dx.doi.org/10.12731/wsd-2014-6.1-16.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Yin, Hang, Francisco S. Melo, Ana Paiva, and Aude Billard. "An ensemble inverse optimal control approach for robotic task learning and adaptation." Autonomous Robots 43, no. 4 (2018): 875–96. http://dx.doi.org/10.1007/s10514-018-9757-y.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Malik, Robi, and Patrícia N. Pena. "Optimal Task Scheduling in a Flexible Manufacturing System using Model Checking." IFAC-PapersOnLine 51, no. 7 (2018): 230–35. http://dx.doi.org/10.1016/j.ifacol.2018.06.306.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Misra, Sudip, Bernd E. Wolfinger, M. P. Achuthananda, Tuhin Chakraborty, Sankar N. Das, and Snigdha Das. "Auction-Based Optimal Task Offloading in Mobile Cloud Computing." IEEE Systems Journal 13, no. 3 (2019): 2978–85. http://dx.doi.org/10.1109/jsyst.2019.2898903.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

FENG, JIANFENG, XIAOJIANG CHEN, HENRY C. TUCKWELL, and ELENI VASILAKI. "SOME OPTIMAL STOCHASTIC CONTROL PROBLEMS IN NEUROSCIENCE — A REVIEW." Modern Physics Letters B 18, no. 21n22 (2004): 1067–85. http://dx.doi.org/10.1142/s0217984904007542.

Full text

Abstract:

Nervous systems are probability machines and, as such, modeling their activities should incorporate stochastic processes. In this review, we present two examples of optimal stochastic control problems with an analytic methodology on how to find optimal signals. The first example deals with neuronal activity and the second example is concerned with a higher level task: arm movement. In both cases we find optimal signals for particular tasks and find our results in agreement with the experimental Fitts Law.

APA, Harvard, Vancouver, ISO, and other styles

32

Goldenberg, A. A., J. A. Apkarian, and H. W. Smith. "A New Approach to Kinematic Control of Robot Manipulators." Journal of Dynamic Systems, Measurement, and Control 109, no. 2 (1987): 97–103. http://dx.doi.org/10.1115/1.3143843.

Full text

Abstract:

A new approach for solving the inverse kinematics problem iteratively is presented. The solution is based on the recursive estimation of a kinematics operator which maps the task space coordinates into joint coordinates. The recursive estimation is based on least square approximation. For controlling the robot, the solution (Joint coordinates) must be compensated to achieve an arbitrarily small error (in least square sense) of the desired task space coordinates. The compensation is provided by closed loop feedback of task space coordinates using an optimal control approach.

APA, Harvard, Vancouver, ISO, and other styles

33

Silvestrini, Nicolas, Elodie Vuignier, Alain Matthey, and Valérie Piguet. "The Perception of Available Resources Influences the After-Effect of Cognitive Control on Cognitive Performance and Pain." Social Psychology 50, no. 5-6 (2019): 332–44. http://dx.doi.org/10.1027/1864-9335/a000386.

Full text

Abstract:

Abstract. In two experiments, we investigated the impact of perceived available cognitive resources using a sequential-task paradigm. First, participants worked on an easy or difficult cognitive task. Then, they received a cue suggesting that their cognitive resources were still optimal or they did not receive any information on their resources. Subsequently, they worked on a second difficult cognitive task (Experiment 1) or received painful electrical stimulations (Experiment 2). We predicted that the cue on optimal resources would neutralize the effect of the first difficult task on subsequent cognitive performance and pain. Overall, results supported our predictions. We interpret these findings as showing an important role of perceived available resources in the after-effect induced by the sequential-task paradigm.

APA, Harvard, Vancouver, ISO, and other styles

34

Luo, Zhong Ming, Zhuo Fu Liu, Fan Wang, and Ling Sen Lin. "Nonlinear Ethanol Gasoline Optimal Control System Based on Hammerstein Model." Advanced Materials Research 765-767 (September 2013): 1889–92. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1889.

Full text

Abstract:

In this paper, a Hammerstein model based on forward feedback neural networks was proposed to tackle the optimal control of a nonlinear MISO system. The method offers a solution to the optimization of internal models. The optimal control with the preset value was implemented under both static and dynamic optimal indices. The simulation results showed that the algorithm can fulfill the task of blending ethanol and gasoline effectively.

APA, Harvard, Vancouver, ISO, and other styles

35

Chhabra, Manu, and Robert A. Jacobs. "Properties of Synergies Arising from a Theory of Optimal Motor Behavior." Neural Computation 18, no. 10 (2006): 2320–42. http://dx.doi.org/10.1162/neco.2006.18.10.2320.

Full text

Abstract:

We consider the properties of motor components, also known as synergies, arising from a computational theory (in the sense of Marr, 1982) of optimal motor behavior. An actor's goals were formalized as cost functions, and the optimal control signals minimizing the cost functions were calculated. Optimal synergies were derived from these optimal control signals using a variant of nonnegative matrix factorization. This was done using two different simulated two-joint arms—an arm controlled directly by torques applied at the joints and an arm in which forces were applied by muscles—and two types of motor tasks—reaching tasks and via-point tasks. Studies of the motor synergies reveal several interesting findings. First, optimal motor actions can be generated by summing a small number of scaled and time-shifted motor synergies, indicating that optimal movements can be planned in a low-dimensional space by using optimal motor synergies as motor primitives or building blocks. Second, some optimal synergies are task independent—they arise regardless of the task context—whereas other synergies are task dependent—they arise in the context of one task but not in the contexts of other tasks. Biological organisms use a combination of task-independent and task-dependent synergies. Our work suggests that this may be an efficient combination for generating optimal motor actions from motor primitives. Third, optimal motor actions can be rapidly acquired by learning new linear combinations of optimal motor synergies. This result provides further evidence that optimal motor synergies are useful motor primitives. Fourth, synergies with similar properties arise regardless if one uses an arm controlled by torques applied at the joints or an arm controlled by muscles, suggesting that synergies, when considered in “movement space,” are more a reflection of task goals and constraints than of fine details of the underlying hardware.

APA, Harvard, Vancouver, ISO, and other styles

36

D. Apale, Tejal, and Ajay B. Patil. "Optimization study of fuzzy parametric uncertain system." IAES International Journal of Artificial Intelligence (IJ-AI) 8, no. 1 (2019): 14. http://dx.doi.org/10.11591/ijai.v8.i1.pp14-25.

Full text

Abstract:

This paper deals with the analysis and design of the optimal robust controller for the fuzzy parametric uncertain system. An LTI system in which coefficients depends on parameters described by a fuzzy function is called as fuzzy parametric uncertain system. By optimal control design, we get control law and feedback gain matrix which can stabilize the system. The robust controller design is a difficult task so we go for the optimal control approach. The system can be converted into state space controllable canonical form with the α-cut property fuzzy. For optimal control design, we find control law and get the feedback gain matrix which can stabilize the system and optimizes the cost function. Stability analysis is done by using the Kharitonov theorem and Lyapunov-Popov method. The proposed method applied to a response of Continuous Stirred Tank Reactor (CSTR).

APA, Harvard, Vancouver, ISO, and other styles

37

Zacharia, P. Th, and N. A. Aspragathos. "Optimal robot task scheduling based on genetic algorithms." Robotics and Computer-Integrated Manufacturing 21, no. 1 (2005): 67–79. http://dx.doi.org/10.1016/j.rcim.2004.04.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Alguliev, Rasim Magamed ogly, Ramiz Magamed ogly Aliguliev, and Rashid Kurbanali ogly Alekperov. "An Approach to Optimal Task Assignment in a Distributed System." Journal of Automation and Information Sciences 36, no. 10 (2004): 51–55. http://dx.doi.org/10.1615/jautomatinfscien.v36.i10.60.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Van den Broek, B., W. Wiegerinck, and B. Kappen. "Graphical Model Inference in Optimal Control of Stochastic Multi-Agent Systems." Journal of Artificial Intelligence Research 32 (May 16, 2008): 95–122. http://dx.doi.org/10.1613/jair.2473.

Full text

Abstract:

In this article we consider the issue of optimal control in collaborative multi-agent systems with stochastic dynamics. The agents have a joint task in which they have to reach a number of target states. The dynamics of the agents contains additive control and additive noise, and the autonomous part factorizes over the agents. Full observation of the global state is assumed. The goal is to minimize the accumulated joint cost, which consists of integrated instantaneous costs and a joint end cost. The joint end cost expresses the joint task of the agents. The instantaneous costs are quadratic in the control and factorize over the agents. The optimal control is given as a weighted linear combination of single-agent to single-target controls. The single-agent to single-target controls are expressed in terms of diffusion processes. These controls, when not closed form expressions, are formulated in terms of path integrals, which are calculated approximately by Metropolis-Hastings sampling. The weights in the control are interpreted as marginals of a joint distribution over agent to target assignments. The structure of the latter is represented by a graphical model, and the marginals are obtained by graphical model inference. Exact inference of the graphical model will break down in large systems, and so approximate inference methods are needed. We use naive mean field approximation and belief propagation to approximate the optimal control in systems with linear dynamics. We compare the approximate inference methods with the exact solution, and we show that they can accurately compute the optimal control. Finally, we demonstrate the control method in multi-agent systems with nonlinear dynamics consisting of up to 80 agents that have to reach an equal number of target states.

APA, Harvard, Vancouver, ISO, and other styles

40

Choi, Byoung Wook, Jong Hwa Won, and Myung Jin Chung. "Optimal redundancy resolution of a kinematically redundant manipulator for a cyclic task." Journal of Robotic Systems 9, no. 4 (1992): 481–503. http://dx.doi.org/10.1002/rob.4620090404.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Zhang, Ziyong, Xiaoling Xu, Jinqiang Cui, and Wei Meng. "Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement." Sensors 21, no. 7 (2021): 2400. http://dx.doi.org/10.3390/s21072400.

Full text

Abstract:

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

APA, Harvard, Vancouver, ISO, and other styles

42

Osu, Rieko, Naoki Kamimura, Hiroshi Iwasaki, et al. "Optimal Impedance Control for Task Achievement in the Presence of Signal-Dependent Noise." Journal of Neurophysiology 92, no. 2 (2004): 1199–215. http://dx.doi.org/10.1152/jn.00519.2003.

Full text

Abstract:

There is an infinity of impedance parameter values, and thus different co-contraction levels, that can produce similar movement kinematics from which the CNS must select one. Although signal-dependent noise (SDN) predicts larger motor-command variability during higher co-contraction, the relationship between impedance and task performance is not theoretically obvious and thus was examined here. Subjects made goal-directed, single-joint elbow movements to either move naturally to different target sizes or voluntarily co-contract at different levels. Stiffness was estimated as the weighted summation of rectified EMG signals through the index of muscle co-contraction around the joint (IMCJ) proposed previously. When subjects made movements to targets of different sizes, IMCJ increased with the accuracy requirements, leading to reduced endpoint deviations. Therefore without the need for great accuracy, subjects accepted worse performance with lower co-contraction. When subjects were asked to increase co-contraction, the variability of EMG and torque both increased, suggesting that noise in the neuromotor command increased with muscle activation. In contrast, the final positional error was smallest for the highest IMCJ level. Although co-contraction increases the motor-command noise, the effect of this noise on the task performance is reduced. Subjects were able to regulate their impedance and control endpoint variance as the task requirements changed, and they did not voluntarily select the high impedance that generated the minimum endpoint error. These data contradict predictions of the SDN-based theory, which postulates minimization of only endpoint variance and thus require its revision.

APA, Harvard, Vancouver, ISO, and other styles

43

Omran, Ashraf, and Ayman Kassem. "Optimal task space control design of a Stewart manipulator for aircraft stall recovery." Aerospace Science and Technology 15, no. 5 (2011): 353–65. http://dx.doi.org/10.1016/j.ast.2010.08.009.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Bakar, R. A., and J. Watada. "Biological computation of optimal task arrangement for a flexible machining cell." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 222, no. 6 (2008): 605–18. http://dx.doi.org/10.1243/09596518jsce487.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Borodin, Allan, Nathan Linial, and Michael E. Saks. "An optimal on-line algorithm for metrical task system." Journal of the ACM 39, no. 4 (1992): 745–63. http://dx.doi.org/10.1145/146585.146588.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

SON, CHANGMAN. "COMPARISON OF OPTIMAL PATH PLANNING ALGORITHMS FOR INTELLIGENT CONTROL OF ROBOTIC PART ASSEMBLY TASK." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 05 (2010): 621–44. http://dx.doi.org/10.1142/s0218488510006726.

Full text

Abstract:

Two intelligent part-bringing (path planning or finding) algorithms, to bring a part from an initial position to an assembly hole or a receptacle (target or destination) for a purpose of part mating, related to a robotic part assembly task are introduced. These algorithms are then compared through simulations and several criteria. An entropy function, which is a useful measure of the variability and the information in terms of uncertainty, is introduced to measure its overall performance of a task execution related to the part-bringing task. Fuzzy set theory, well-suited to a management of uncertainty, is introduced to address an uncertainty associated with the part-bringing procedure. A degree of uncertainty associated with a part-bringing is used as an optimality criterion, or cost function, e.g. minimum fuzzy entropy, for a specific task execution. It is shown that the machine organizer using a sensor system can intelligently determine an optimal control value, based on explicit performance criteria, to overcome environmental uncertainty. The algorithms use knowledge processing functions such as machine reasoning, planning, inferencing, learning, and decision-making. The results show the effectiveness of the proposed approaches.

APA, Harvard, Vancouver, ISO, and other styles

47

Jackson, Ilya, Jurijs Tolujevs, and Zhandos Kegenbekov. "Review of Inventory Control Models: A Classification Based on Methods of Obtaining Optimal Control Parameters." Transport and Telecommunication Journal 21, no. 3 (2020): 191–202. http://dx.doi.org/10.2478/ttj-2020-0015.

Full text

Abstract:

AbstractInventory control has been a major point of discussion in industrial engineering and operations research for over 100 years. Various advanced numerical methods can be used for solving inventory control problems, which makes it a highly multidisciplinary filed attracting researchers from different academic disciplines. This fact makes it a daunting task to subsume the gargantuan spectrum of literature related to inventory control theory in one treatise. In light of this fact, this paper focuses on the timeline of inventory control models with respect to methodologies behind deriving optimal control parameters. Such methodologies include analytical approaches, optimal control theory, dynamic programming, simulation-based optimization and metamodel-based optimization.

APA, Harvard, Vancouver, ISO, and other styles

48

Németh, Balázs, Péter Gáspár, and Tamás Hegedűs. "Optimal Control of Overtaking Maneuver for Intelligent Vehicles." Journal of Advanced Transportation 2018 (December 31, 2018): 1–11. http://dx.doi.org/10.1155/2018/2195760.

Full text

Abstract:

In the paper a hierarchical overtaking strategy, which is a driver assistance function or rather an autonomous function in electric/autonomous vehicles, is proposed. The solution uses speed and acceleration signals from the surrounding vehicles. These signals are processed with clustering methods in order to achieve probability density functions and predict their expected motion. The strategy includes several additional layers, such as decision making concerning the maneuver, the computation of the required trajectory, and the tracking control of the vehicle. Trajectory generation is formed as an optimization task, which is able to include the prediction model of the surrounding vehicles in the constraints. A robust Linear Parameter Varying (LPV) control design method is proposed to guarantee the tracking of the computed reference. The proposed strategy is able to guarantee the safe motion of the vehicles and handle the interactions with the other traffic participants.

APA, Harvard, Vancouver, ISO, and other styles

49

Borkovskaya, Victoria G. "Complex Models of Active Control Systems at the Modern Developing Enterprises." Advanced Materials Research 945-949 (June 2014): 3012–15. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.3012.

Full text

Abstract:

Management Science develops naturally through the development of any science - from simple to complex, from simple to complex controls production control systems, spacecraft, etc. Now science has approached the management is perhaps the most difficult task – to control the person, team, organization, society. The fact that a man unlike any most complex technical system has the properties of activity, ie, its own goals, the foresight to achieve their goals is able to distort the information transmitted by the management body (able to deceive), and is also able to deliberately fail to perform prescribed tasks (plans). The task of managing such active objects and is the essence of the theory of active systems. This article briefly describes the stages in the development of the theory of optimal problem in modern enterprise, which develops, including technical and economic issues tasking and optimal allocation of costs between projects.

APA, Harvard, Vancouver, ISO, and other styles

50

Kokkinis, T., and M. Sahraian. "Inverse Dynamics of a Flexible Robot Arm by Optimal Control." Journal of Mechanical Design 115, no. 2 (1993): 289–93. http://dx.doi.org/10.1115/1.2919190.

Full text

Abstract:

The problem of end-point positioning of flexible arms is discussed. Because of the nonminimum phase nature of the problem, inversion fails to produce bounded joint torques. Bounded noncausal joint torques for achieving the task of end-point tracking for a multilink arm are found using optimal control theory. The torques obtained have no high-frequency content, and are suitable for practical applications. The method is illustrated by simulation of a single-link arm, for which stability and robustness considerations for design are given.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!