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Dissertations / Theses on the topic 'Nonlinear control systems'

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Published: 4 June 2021

Last updated: 1 February 2022

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1

Grönberg, Fredrik. "Crowd Control of Nonlinear Systems." Thesis, KTH, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138438.

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We study a multi-agent system in R2 where agents have unicycle dynamics with time varying speed and control inputs corresponding to acceleration and angular velocity. The system has a dynamic communication topology based on proximity. We propose a novel decentralized control algorithm derived from a double integrator model using a pairwise potential function. By using an energy function we show that a leaderless system converges to a set where connected agents have equal direction and velocity and potential contributions to the control action cancel each other out. The concept of formation density is defined and studied by numerical simulation. We find a relation between parameters of the controller and the system that makes the system converge to a formation with low density, corresponding to agents being at appropriate distances from each other, also when agents are not restricted to communicating only with their closest neighbors. The algorithm is tested for a system with leaders and properties of this system are investigated numerically. The results confirm that the proportion of leaders needed to guide a certain proportion of the agent in average is nonlinear and decreasing with respect to the number of agents.

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2

Nevistić, Vesna. "Constrained control of nonlinear systems." Online version, 1997. http://bibpurl.oclc.org/web/26200.

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3

Tatlicioglu, Enver. "Control of nonlinear mechatronic systems." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1193079994/.

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4

Samavat, Mohmoud. "Robust control of nonlinear systems." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327647.

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5

Lei, Hao. "Universal Output Feedback Control of Nonlinear Systems." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1193422144.

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6

Abbaspour, Ali Reza. "Active Fault-Tolerant Control Design for Nonlinear Systems." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3917.

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Faults and failures in system components are the two main reasons for the instability and the degradation in control performance. In recent decades, fault-tolerant control (FTC) approaches were introduced to improve the resiliency of the control system against faults and failures. In general, FTC techniques are classified into two major groups: passive and active. Passive FTC systems do not rely on the fault information to control the system and are closely related to the robust control techniques while an active FTC system performs based on the information received from the fault detection and isolation (FDI) system, and the fault problem will be tackled more intelligently without affecting other parts of the system. This dissertation technically reviews fault and failure causes in control systems and finds solutions to compensate for their effects. Recent achievements in FDI approaches, and active and passive FTC designs are investigated. Thorough comparisons of several different aspects are conducted to understand the advantages and disadvantages of different FTC techniques to motivate researchers to further developing FTC, and FDI approaches. Then, a novel active FTC system framework based on online FDI is presented which has significant advantages in comparison with other state of the art FTC strategies. To design the proposed active FTC, a new FDI approach is introduced which uses the artificial neural network (ANN) and a model based observer to detect and isolate faults and failures in sensors and actuators. In addition, the extended Kalman filter (EKF) is introduced to tune ANN weights and improve the ANN performance. Then, the FDI signal combined with a nonlinear dynamic inversion (NDI) technique is used to compensate for the faults in the actuators and sensors of a nonlinear system. The proposed scheme detects and accommodates faults in the actuators and sensors of the system in real-time without the need of controller reconfiguration. The proposed active FTC approach is used to design a control system for three different applications: Unmanned aerial vehicle (UAV), load frequency control system, and proton exchange membrane fuel cell (PEMFC) system. The performance of the designed controllers are investigated through numerical simulations by comparison with conventional control approaches, and their advantages are demonstrated.

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7

Brunke, Shelby Scott. "Nonlinear filtering and system identification algorithms for autonomous systems /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/7095.

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8

Ashman, J. A. "Adaptive control of uncertain nonlinear systems." Thesis, University of Bath, 1994. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260256.

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9

Tse, Wilfred See Foon. "Linear equivalents of nonlinear systems." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26652.

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Consider the following nonlinear system [Formula Omitted] where ϰ ∈ Rⁿ, f, ℊ₁,…,ℊｍ are C∞ function in Rⁿ and ℎ is a C∞ function in R⍴, all defined on a neighborhood of 0. The problem of finding a necessary and sufficient condition such that system (1) can be transformed to a linear controllable system by a state coordinate change and feedback has been studied quite well. In this thesis, we first discuss a few different approaches to this problem and eventually we will show that the slightly different versions of the necessary and sufficient condition discovered are equivalent. Next we consider system (1) with all սi,= 0 together with system (2), and study the dual problem of transforming it to a linear observable system by a state and output coordinate change. Finally, we consider briefly system (l) and (2) with nonzero սi and study the problem of transforming it to a linear system that is both completely controllable and observable. Examples are given and applications to local stabilization and estimation are discussed.
Science, Faculty of
Mathematics, Department of
Graduate

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10

Lemch, Ekaterina S. "Nonlinear and hierarchical hybrid control systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0032/NQ64600.pdf.

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11

Chryssochoos, Ioannis. "Optimization based control of nonlinear systems." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399165.

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12

Zhu, Quan Min. "Identification & control of nonlinear systems." Thesis, University of Warwick, 1989. http://wrap.warwick.ac.uk/62723/.

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This thesis investigates some problems on nonlinear system identification, parameter estimation, and signal processing. Random signal spectral analysis and system frequency response estimation are studied from incomplete time series. Both recursive and direct estimators are presented based on either an unbiased or minimum mean square error criterion. Nonlinear system identification and parameter estimation are studied. A quantisation technique is developed to give a clear geometrical interpretation for structure detection and parameter estimation. A new concept, state amplitude distance between current and previous operating states, is introduced, and results in a Variable Weighted Least Squares (VWLS) algorithm. A modified version makes on-line application possible. Jump resonance is predicted by the VWLS algorithm as one of the applications. Self-tuning controllers, including a nonlinear general predictive controller and a nonlinear deadbeat controller, are designed. A vector backward shift operator is defined to simplify the expression of the Hammerstein model, and is introduced to analyse the general feedback controller design problem for nonlinear plant described by the Hammerstein model. A fast root-solver developed facilitates nonlinear model treatment in on-line applications. Theoretical results are confirmed by simulation studies.

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13

Vela, Patricio Antonio Burdick Joel Wakeman. "Averaging and control of nonlinear systems /." Diss., Pasadena, Calif. : California Institute of Technology, 2003. http://resolver.caltech.edu/CaltechETD:etd-05282003-094253.

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14

Chudoung, Jerawan. "Robust Control for Hybrid, Nonlinear Systems." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26983.

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We develop the robust control theories of stopping-time nonlinear systems and switching-control nonlinear systems. We formulate a robust optimal stopping-time control problem for a state-space nonlinear system and give the connection between various notions of lower value function for the associated game (and storage function for the associated dissipative system) with solutions of the appropriate variational inequality (VI). We show that the stopping-time rule can be obtained by solving the VI in the viscosity sense. It also happens that a positive definite supersolution of the VI can be used for stability analysis. We also show how to solve the VI for some prototype examples with one-dimensional state space. For the robust optimal switching-control problem, we establish the Dynamic Programming Principle (DPP) for the lower value function of the associated game and employ it to derive the appropriate system of quasivariational inequalities (SQVI) for the lower value vector function. Moreover we formulate the problem in the L₂-gain/dissipative system framework. We show that, under appropriate assumptions, continuous switching-storage (vector) functions are characterized as viscosity supersolutions of the SQVI, and that the minimal such storage function is equal to the lower value function for the game. We show that the control strategy achieving the dissipative inequality is obtained by solving the SQVI in the viscosity sense; in fact this solution is also used to address stability analysis of the switching system. In addition we prove the comparison principle between a viscosity subsolution and a viscosity supersolution of the SQVI satisfying a boundary condition and use it to give an alternative derivation of the characterization of the lower value function. Finally we solve the SQVI for a simple one-dimensional example by a direct geometric construction.
Ph. D.

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15

Sangelaji, Zahra. "Angular representations of nonlinear control systems." Thesis, University of Sheffield, 2005. http://etheses.whiterose.ac.uk/14880/.

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The aim of this thesis is to examine and extend the angular approach, which is a new approach for designing control and analysis of nonlinear systems. In this approach, the system is converted into two subsystems. One subsystem, the so-called spherical subsystem, is defined on a sphere, whilst the other subsystem, the radial subsystem, is one dimensional. A suitable control is designed using the radial subsystem. Various new methods are presented for the stabilisation and control design of a general class of nonlinear systems, based upon the angular approach. The advantage of this approach is that the stabilisation and control design problem of a nonlinear system is replaced by a one-dimensional control design and stabilisation problem. In addition, the control design using the angular approach is a straightforward, systematic method which is applicable to a wide class of nonlinear systems with and without uncertainty. Whenever the input map of the radial subsystem is zero, the radial control is not accessible and the control should be modified such that the defined control is accessible everywhere within the entire operating region. Several methods are considered for modifying the radial control including dynamical radial method. An adaptive angular method is also proposed to design an angular control for stabilisation of a nonlinear system with unknown parameters. The optimal control of nonlinear systems based upon the associated angular approach is also studied in this thesis. After decoupling the two associated (radial and spherical) subsystems and considering only the radial system, a finite-horizon radial optimal control is designed which minimises the appropriate radial cost function. Then the successive approximation technique is introduced in which the equations are replaced by a sequence of linear, time-varying approximations. The resulting optimal control is then applied to the original angular system. This control forces the original angular system to an equilibrium point. In addition, the control design and stabilisation problem for multi-input nonlinear systems using the angular approach is also studied.

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16

Gao, Yang. "Adaptive fuzzy control of nonlinear systems." Mémoire, Université de Sherbrooke, 2006. http://savoirs.usherbrooke.ca/handle/11143/1335.

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Fuzzy logic provides human reasoning capabilities to capture uncertainties that cannot be described by precise mathematical models. An adaptive fuzzy system is a fuzzy logic system equipped with a learning algorithm. A"learning system" possesses the capability to improve its performance over time by interacting with its environment, so an adaptive control system has the ability to improve the performance of the closed-loop system by generating command inputs to the plant and utilizing feedback information from the plant. This thesis proposes a fast approach for system modeling by neuro-fuzzy networks (NFNs), which can successfully model the nonlinear system dynamics and its uncertainties. This algorithm can construct a system model by NFN, i.e., fuzzy rules can be generated automatically in the learning process from training data without partitioning the input space and selecting initial parameters a priori. This thesis presents an adaptive fuzzy control method of nonlinear systems using the NFN controller, which can be constructed by the fast learning algorithm proposed in this thesis. In simulation studies, an inverted pendulum system can track the desired trajectory very well and the control system has good robustness to disturbances using the adaptive control method proposed. The inverted pendulum is controlled by the proposed adaptive fuzzy control method, classical PID control method and nonadaptive fuzzy control method respectively; the control results show that the adaptive fuzzy control system has the best performances among the three control systems in terms of transient and steady-state results.

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17

Rysdyk, Rolf T. "Adaptive nonlinear flight control." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/12108.

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18

Mathew, Michael Ian. "Design of nonlinear sampled-data systems." Thesis, Coventry University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.480606.

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19

Vaziri, Hamaneh Seyed Vahid. "Dynamics and control of nonlinear engineering systems." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=228062.

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This thesis is focused on the dynamics and control of nonlinear engineering systems. A developed approach is applied to three specific problems: suppression of torsional vibrations occurring in a drill-string, lateral vibrations on an unbalanced rotor and vibrational energy extraction from rotating pendulum systems. The first problem deals with drill-string torsional vibrations while drilling, which is conducted in the experimental drilling rig developed at University of Aberdeen. A realistic model of the experimental setup is then constructed, taking into account the dynamics of the drill-string and top motor. Physical parameters of the experimental drilling rig are estimated in order to calibrate the model to ensure the correspondence of the research results to the experimental conditions. Consequently, a control method is introduced to suppress torsional and stick-slip oscillations exhibited in the experimental drilling rig. The experimental and numerical results considering delay of the actuator are shown to be in close agreement, including the success of the controller in significantly reducing the vibrations. In the second problem a soft impact oscillator approach is used to study the dynamics of the asymmetric Jeffcott rotor. A realistic model of the experimental setup is developed, taking into account an asymmetric physical configuration in rotor part as well as snubber rig. Several experimental bifurcation diagrams are conducted with different conditions in range around the grazing point. Experimental and numerical results based on the proposed model are compared and shown to be in close agreement. The last problem relates to initiating and maintaining the rotational motion of a parametric pendulum as an energy harvesting system. Several possible control methods to initiate and maintain the rotational motion of a harmonically-excited pendulum are proposed and then verified experimentally. The time-delayed feedback method is shown to maintain quite well the rotational motion of a sinusoidally excited parametric pendulum, even in the presence of noise. A control method for the wave-excited pendulum system is then suggested and tested in order to increase the probability of its rotational motion. This proposed control method succeeds in significantly raising the probability of rotational motion of the wave-excited pendulum.

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20

Mohd, Isira Ahmad Sadhiqin Bin. "Consensus control of a class of nonlinear systems." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/consensus-control-of-a-class-of-nonlinear-systems(462b2f1a-d08b-4c52-9f3e-c2dcb7257acc).html.

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This dissertation aims at solving the consensus control problem of multi-agent systems with Lipschitz nonlinearity. This depends on the design of the controller that enables each agent or subsystem in multi-agent systems with Lipschitz nonlinearity to reach consensus; using the understanding of the agents' connection network from the knowledge of graph theory as well as the control system design strategy. The objective is achieved by designing a type of distributed control, namely the consensus control, which manipulates the relative information of each agent in a multi-agent systems in order to arrive at a single solution. In addition, containment control is also developed to solve containment problem. It is an extension of consensus control via leader-follower configuration, aimed at having each agent contained by multiple leaders in a multi-agent systems with Lipschitz nonlinearity. Four types of controllers are proposed - state-feedback consensus controller, observer-based consensus controller, state-feedback containment controller and observer-based containment controller; each provides the stability conditions based on Lyapunov stability analysis in time domain which enabled each agent or subsystem to reach consensus. The observer-based controllers are designed based on the consensus observer that is related to Luenberger observer. Linear Matrix Inequality (LMI) and Algebraic Riccati Equation (ARE) are utilized to obtain the solutions for the stability conditions. The simulation results of the proposed controllers and observers have been carried out to prove their theoretical validity. Several practical examples of flexible robot arm simulations are included to further validate the theoretical aspects of the thesis.

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21

Leitner, Jesse. "Helicopter nonlinear control using adaptive feedback linearization." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/11985.

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22

Lehman, Bradley M. "Vibrational control of nonlinear time delay systems." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/14718.

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23

McCabe, Andrew Peter. "Proportional-integral-plus control of nonlinear systems." Thesis, Lancaster University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289039.

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24

Banaszuk, Andrzej. "Approximate feedback linearization of nonlinear control systems." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/29838.

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25

Du, Suguo. "Fault detection for polynomial nonlinear systems." Thesis, Coventry University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247208.

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26

Cheung, Wan Sup. "Identification, stabilisation and control of nonlinear systems using neural network-based parametric nonlinear modelling." Thesis, University of Southampton, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333732.

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27

Vocke, Tanja. "On the control of nonlinear dynamical systems." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=962791733.

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28

Zhang, Xin. "Nonlinear phenomena and control in power systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0023/MQ30706.pdf.

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29

Lei, Hao. "Universal ouput feedback control of nonlinear systems." online version, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1193422144.

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30

Kaliora, Georgia. "Control of nonlinear systems with bounded signals." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.397289.

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31

Mills, Russell Edward. "Robust backstepping control of nonlinear uncertain systems." Thesis, University of Sheffield, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246989.

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32

Sharkey, P. M. "Composite control of nonlinear singularly perturbed systems." Thesis, University of Strathclyde, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382486.

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33

Feng, Ming. "Local modelling and control of nonlinear systems." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326788.

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34

Cho, Dong-Il. "Nonlinear control methods for automotive powertrain systems." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/14682.

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35

Sangwin, Christopher James. "Uncertain dynamical systems and nonlinear adaptive control." Thesis, University of Bath, 2000. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341671.

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36

Tigrek, Tuba. "Nonlinear adaptive optimal control of HVAC systems." Thesis, University of Iowa, 2001. https://ir.uiowa.edu/etd/3429.

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37

Shukla, Himanshu. "Nonlinear Analysis and Control of Aeroelastic Systems." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71468.

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Presence of nonlinearities may lead to limit cycle oscillations (LCOs) in aeroelastic systems. LCOs can result in fatigue in wings leading to catastrophic failures. Existence of LCOs for velocities less than the linear flutter velocity has been observed during flight and wind tunnel tests, making such subcritical behavior highly undesirable. The objective of this dissertation is to investigate the existence of subcritical LCOs in aeroelastic systems and develop state feedback controllers to suppress them. The research results are demonstrated on a two degree of freedom airfoil section model with stiffness nonlinearity. Three different approaches are developed and discussed. The first approach uses a feedback linearization controller employing the aeroelastic modal coordinates. The use of modal coordinates results in a system which is linearly decoupled making it possible to avoid cancellation of any linear terms when compared to existing feedback linearization controllers which use the physical coordinates. The state and control costs of the developed controller are compared to the costs of the traditional feedback linearization controllers. Second approach involves the use of nonlinear normal modes (NNMs) as a tool to predict LCO amplitudes of the aeroelastic system. NNM dynamics along with harmonic balance method are used to generate analytical estimates of LCO amplitude and its sensitivities with respect to the introduced control parameters. A multiobjective optimization problem is solved to generate optimal control parameters which minimize the LCO amplitude and the control cost. The third approach uses a nonlinear state feedback control input obtained as the solution of a multiobjective optimization problem which minimizes the difference between the LCO commencement velocity and the linear flutter velocity. The estimates of LCO commencement velocity and its sensitivities are obtained using numerical continuation methods and harmonic balance methods. It is shown that the developed optimal controller eliminates any existing subcritical LCOs by converting them to supercritical LCOs.
Ph. D.

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38

Dehesa, Valencia Julio César. "INTERVAL ROBUST CONTROL FOR NONLINEAR FLAT SYSTEMS." Doctoral thesis, Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/27724.

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Esta tesis se enfoca principalmente en el control robusto de sistemas no lineales planos. El objetivo principal es determinar una familia de controladores robustos con la finalidad de asegurar el cumplimiento de un conjunto de especificaciones deseadas bajo incertidumbre paramétrica en el proceso. La familia de controladores robustos se determina con un nuevo enfoque de control robusto posibilistico conjuntamente con la teoría de los sistemas planos. Las especificaciones e incertidumbre paramétrica se establecen mediante intervalos. Se aplican la Aritmética Intervalar Modal y el Análisis de Algoritmos de Inversión de Conjuntos Cuantificados para encontrar los conjuntos de soluciones. Se resuelven diferentes problemas de control robusto tales como: Conjuntos de soluciones referidos a las especificaciones alcanzables por una familia de controladores, así como la determinación de la incertidumbre máxima admitida por un controlador nominal. En esta tesis se desarrolla una nueva metodología de análisis de robustez de controladores basados en platitud diferencial, donde el uso de una pre alimentación es requerida. La metodología desarrollada es aplicada a diferentes procesos, específicamente a bioreactores fed-batch, dada la importancia de estos reactores de alta densidad de tanque agitado para la producción industrial eficiente de proteínas y enzimas.
Dehesa Valencia, JC. (2013). INTERVAL ROBUST CONTROL FOR NONLINEAR FLAT SYSTEMS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/27724
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Boccia, Andrea. "Optimization based control of nonlinear constrained systems." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24700.

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This thesis is in the field of Optimal Control. It addresses research questions concerning both the properties of optimal controls and also schemes for control system stabilization based on the solution of optimal control problems. The first part is concerned with the derivation of necessary conditions of optimality for two classes of optimal control problems not covered by earlier theory. The first is the class of optimal control problems with a combination of mixed control-state constraints and pure state constraints in which the dynamics are described by a differential inclusion under weaker hypotheses than have previously been considered. The second is the class of optimal control problems in which the dynamics take the form of a non-smooth differential equation with delays, and where the end-time is included in the decision variables. We shall demonstrate that these new optimality conditions lead to algorithms for solution of certain optimal control problems not amenable to earlier theory. Model Predictive Control (MPC) is an approach to control system design based on solving, at each control update time, an optimal control problem. This is the subject matter of the second part of the thesis. We derive new MPC algorithms for constrained linear and nonlinear systems which, in certain significant respect, are simpler to implement than standard schemes, and which achieve performance specification under more general conditions than has previously been demonstrated. These include stability and feasibility.

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40

Tayamon, Soma. "Nonlinear system identification with applications to selective catalytic reduction systems." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-186963.

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The stringent regulations on the emissions levels of heavy duty vehicles create a demand for new methods of reducing harmful emissions from the engine. In order to be able to follow these increasingly stricter legislations, complex aftertreatment systems are used. Achievement of optimal performance of these systems requires accurate models that can be used for control design. As a result, the interest in modelling and control of aftertreatment systems has increased. This thesis deals with the modelling of the nitrogen oxide (NOx) emissions from heavy duty vehicles using the selective catalyst as an aftertreatment system for its reduction. The process of the selective catalytic reduction (SCR) is nonlinear since the chemical reactions involved are highly depending on the operating point. The momentary operating point is defined by the driving profile of the vehicle which, for example, includes cold and hot engine starts, highway and urban driving. The purpose of this thesis is to investigate different methods for nonlinear system identification of SCR systems with control in mind. The first two papers contain the theoretical work of this thesis. The first paper deals with improvement of an existing recursive prediction error method (RPEM) where a more accurate discretisation algorithm was used to improve the accuracy of the estimated nonlinear model. The second paper deals with analysis of the convergence properties of the algorithm. For this analysis several conditions were formulated that link the global and local convergence properties of the algorithm to stability properties of an associated differential equation. Global convergence to a stationary point was shown. In the third paper, the RPEM is used for identification of the SCR system and finally the fourth paper a Hammerstein–Wiener model for identification of the SCR system is applied. In both these cases the black-box models could predict the NOx behaviour of the SCR system quite well. The nonlinear models were shown to describe the SCR system more accurately than linear models.

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41

Kozak, Kristopher C. "Robust command generations for nonlinear systems." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/15849.

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42

Lee, James X. "On fuzzy logic systems, nonlinear system identification, and adaptive control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq26881.pdf.

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43

Lee, James X. (James Xiang) Carleton University Dissertation Engineering Mechanical and Aerospace. "On fuzzy logic systems, nonlinear system identification, and adaptive control." Ottawa, 1997.

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44

Nguyen, Canh Quang Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Switching robust adaptive control in nonlinear mechanical systems." Awarded by:University of New South Wales. School of Mechanical & Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/24318.

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This work describes analysis, design, and implementation of a novel switching robust adaptive control (SRAC) method for nonlinear systems. The proposed method takes advantage of both adaptive control (AC) and robust control (RC) methods. SRAC employs one of the methods when this method is advantageous and switches to the other method when the other one becomes the preferred choice. To this end, RC is used to deal with transient effects caused by uncertainties and disturbances. The system switches over to AC for good steady state performance when certain switching criteria are satisfied. If external disturbances become dominant or new uncertainties are introduced while AC is active, the system will switch back to RC. In this manner, the switching process between AC and RC will continue to take place guaranteeing improved performance, robustness, and accuracy for the entire operation of the system. The novel idea behind the proposed method is a smart novel mechanism of bi-directional switching between RC and AC. In this mechanism, the involvement of estimators and switching rules play a decisive part in guaranteeing the smooth switching and the stability of the system. The implementation and design issues of the novel method were first evaluated by simulation on a mass spring system and then on a robot manipulator system. To control these systems with satisfactory performance, nonlinearities and uncertainties have been properly analysed and embedded into models and control algorithms. Simulation results showed the superior performance of the proposed method compared with other control methods. The experimental validation of the proposed method was conducted on a Puma 560 robot manipulator system which was established by joints 2 and 3 of the robot. Extensive comparative experimental results have validated the efficacy and superior performance of the proposed SRAC method over other control methods in the face of uncertainties and disturbances. As part of this work, a comprehensive dynamic model of robotic manipulator in the presence of joint motors, gravitational forces, friction forces and payload has been developed using MAPLE. A systematic design framework for the SRAC method has also been developed.

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45

Li, Liangmin. "Continuous time nonlinear system identification." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341867.

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46

Zhang, Guoming. "Model reference control for nonlinear plants." Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314208.

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47

Noiey, A. Ranjbar. "Sensorless nonlinear control of asynchronous machines." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/844099/.

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An alternative to the existing technique of controlling induction machines - vector control - was investigated. In the new technique, sensorless nonlinear control, the mathematical model of the machine was transformed to a linear form and those states which were not measured (sensed) were reconstructed. It was shown possible to maintain stability despite the errors which the use of observers introduces into the control loop. The investigation is founded primarily on a study of the theory. Demonstration of the proposed scheme has been done mainly by means of simulation. The stability of the computer code for simulation was verified by a study of the stiffness and modes (eigenvalues) of the overall system. Furthermore, modifications to the simulation such as the introduction of noise, were made to increase its validity. The main findings were as follows: 1. In the new technique the decoupling of the speed (torque) and flux control is perfect. 2. The linearised model separates into two subsystems, one mechanical and one electromagnetic. 3. The control scheme is robust against disturbances (step change of load). 4. An asymptotic observer can successfully reconstruct both flux and speed states when the whole system is under the linearisation approach. Therefore sensorless nonlinear control is made possible and effective. 5. By selecting initial value(s) for the estimated state(s) close to the command(s) the transient demand on the power supply is reduced. Thus it may be possible to use smaller and cheaper power converters in a drive system. 6. This technique is also able to counteract some of the model uncertainties resulting from temperature variations. The significance of these findings is as follows: 1. Maximum torque and efficiency are achievable only by the new technique. In contrast, in field-weakening under vector control a near optimum is achievable only at the price of degrading the transient behaviour. 2. Direct measurement of flux and speed is avoided, which has, in practice economic benefit. 3. Although the proposed control technique is more complex than field-oriented control, its stability has been analytically proven and, in addition, the rate of convergence (for both the control and the estimator) is adjustable. 4. A sensitivity investigation shows the robustness of the proposed method when the most critical parameter i.e. the rotor resistance, varies slightly from its nominal value. 5. The simulation approach was developed to the point where it was believed possible to investigate the capability of the proposed technique and to identify potential practical problems with the nonlinear control strategy. Moreover the same code can easily be modified for compiling into a microprocessor, so allowing easy implementation of the scheme. 6.The proposed control is easily implementable in commercial drives due to the modest voltage and current demand, even in the initial transient.

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Sabattini, Lorenzo <1983&gt. "Nonlinear Control Strategies for Cooperative Control of Multi-Robot Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amsdottorato.unibo.it/4465/.

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This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.

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Brus, Linda. "Nonlinear Identification and Control with Solar Energy Applications." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8594.

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Trebi-Ollennu, Ashitey. "Robust nonlinear control, designs using adaptive fuzzy systems." Thesis, Cranfield University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296492.

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