A networked control system (NCS) is a control system where sensors, actuators, and controllers are interconnected over a communication network. This dissertation presents a framework for modeling, stability analysis, optimal control, and bandwidth allocation of the NCS. A ball magnetic-levitation (maglev) system, four DC motor speed-control systems, and a wireless autonomous robotic wheelchair are employed as test beds to illustrate and verify the theoretical results of this dissertation. This dissertation first proposes an output feedback method to stabilize and control the NCSs. The random time delays in the controller-to-actuator and sensor-to-controller links are modeled with two time-homogeneous Markov chains while the packet losses are treated with Dirac delta functions. An asymptotic mean-square stability criterion is established to compensate for the network-induced random time delays and packet losses in the NCS. Then, an algorithm to implement the asymptotic mean-square stability criterion is presented. Experimental results illustrate effectiveness of the proposed output feedback method compared to conventional controllers. The proposed output feedback controller could reduce the errors of the NCS by 13% and 30–40% for the cases without and with data packet losses, respectively. The optimal bandwidth allocation and scheduling of the NCS with nonlinear-programming techniques is also presented in the dissertation. The bandwidth utilization (BU) of each client is defined in terms of its sampling frequency. Two nonlinear approximations, exponential and quadratic approximations, are formulated to describe the system performance governed by discrete-time integral absolute error (DIAE) versus sampling frequency. The optimal sampling frequencies are obtained by solving the approximations with Karush-Kuhn-Tucker (KKT) conditions. Simulation and experimental results are given to verify the effectiveness of the proposed approximations and the bandwidth allocation and scheduling algorithms. In simulations and experiments, the two approximations could maximize the total BU of the NCS up to about 98% of the total available network bandwidth.

The thesis considers the problems of designing a dynamic output feedback controller to discrete time systems with polytopic uncertainty so that the closed-loop systems are DR stable with their transfer matrices having H2 norm and H¡Û norm bounded by a prescribed value ru. The formar part of the thesis provides less conservative LMI conditions for H2 and H¡Û analysis and the output feedback control of discrete system than those appeared in the current research. While the latter part of the thesis extend the current research to DR stable with H2 and H¡Û design. Finally, numerical examples are illustrated to show improvement of the propered result.

This work considers formulation of new classes of adaptive controllers for double-integrator type systems where the underlying system parameters are uncertain and the complete state-vector is not available for feedback. Given the parameter uncertainty within the system model, a "separation principle" cannot generally be invoked towards an observer geared towards reconstruction of the full state vector using only measured variables. In this report, controllers are designed for some important sub-classes of Euler-Lagrange type mechanical systems, where states are physically interpreted as position and velocity variables, and only the position part of the state vector is available as measured output. The typical approach to obtain velocity estimates using position interpolation (also known as dirty differentiation), is known to be strongly susceptible to measurement noise and therefore does not usually represent a robust option for feedback control implementation. The proposed control scheme achieves global asymptotic stability for system dynamics subject to the condition that velocity states appear within the governing dynamics in a linear fashion. This arguably restrictive condition is loosened for the special case of scalar system with friction non-linearity as is typical within hardware implementations. The objective is to study prototypical mechanical systems with non-linearity appearing in the velocity rate equations with the eventual applications envisioned towards the attitude control problem accounting for the gyroscopic non-linearity in the Euler rotational dynamics. Based on classical certainty equivalence approaches for adaptive control, one cannot readily deal with cross terms associated with parameter estimates and unmeasured states in the Lyapunov function derivative in order to make the Lyapunov function negative definite or negative semi-definite. However, employing a new approach, this obstacle is shown in this report to be circumvented for scalar systems. In order to generalize the methodology for higher-order dynamics, a filtered state approach is used. Specifically, an auxiliary variable is introduced which plays an important role in determining restrictions on the control parameters and analyzing the stability. The proposed approach helps to overcome the uniform detectability obstacle. Additionally, this work can be applied to uncertain linear systems where independent control inputs are applied on each of the velocity state dynamics. Lastly, the solution for the scalar is applied to the rotor speed control system and is extended to the case where Coulomb friction is considered in addition to viscous friction. Since a sign function can be approximated as a hyperbolic tangent, the tanh model is used for the Coulomb friction. A controller is developed with the assumption that the coefficients of these frictions are unknown. The proposed control is then verified with Educational Control Product Model 750 Control Moment Gyroscope, and the simulation and actual test results are compared. / text

Numerical methods of designing control systems are currently an active area of research. Convex optimization with linear matrix inequalities (LMIs) is one such method. Control objectives like minimizing the H_2, H_infinity norms, limiting the actuating effort to avoid saturation, pole-placement constraints etc., are cast as LMIs and an optimal feedback controller is found by making use of efficient interior-point algorithms. A full-state feedback controller is designed and implemented in this thesis using this method which then forms the basis for designing a static output feedback (SOF) controller. A profile was generated that relates the change in the SOF control gain matrix required to keep the same value of the generalized H_2 norm of the transfer function from the road disturbance to the actuating effort with the change in the sprung mass of the quarter-car system. The quarter-car system makes use of a linear brushless permanent magnet motor (LBPMM) as an actuator, a linear variable differential transformer (LVDT) and two accelerometers as sensors for feedback control and forms a platform to test these control methodologies. For the full-state feedback controller a performance measure (H_2 norm of the transfer function from road disturbance to sprung mass acceleration) of 2.166*10^3 m/s^2 was achieved ensuring that actuator saturation did not occur and that all poles had a minimum damping ratio of 0.2. The SOF controller achieved a performance measure of 1.707*10^3 m/s^2 ensuring that actuator saturation does not occur. Experimental and simulation results are provided which demonstrate the effectiveness of the SOF controller for various values of the sprung mass. A reduction in the peak-to-peak velocity by 73 percent, 72 percent, and 71 percent was achieved for a sprung mass of 2.4 kg, 2.8 kg, and 3.4 kg, respectively. For the same values of the sprung mass, a modified lead-lag compensator achieved a reduction of 79 percent, 77 percent and, 69 percent, respectively. A reduction of 76 percent and 54 percent in the peak-to-peak velocity was achieved for a sprung mass of 6.0 kg in simulation by the SOF controller and the modified lead-lag compensator, respectively. The gain of the modified lead-lag compensator needs to be recomputed in order to achieve a similar attenuation as that of the SOF controller when the value of the sprung mass is changed. For a sprung mass of 3.4 kg and a suspension spring stiffness of 1640 N/m the peak-to-peak velocity of the sprung mass was attenuated by 42 percent.

Functional Electrical Stimulation (FES) is a technique that applies electrical currents to nervous tissue in order to actively induce muscle contraction. Recent research has shown that FES provides a promising treatment to restore functional tasks due to paralysis caused by spinal cord injury, head injury, and stroke, to mention a few. Therefore, the overarching goal of this research work is to develop FES controllers to enable patients with movement-disorder to control their limbs in a desired manner and, in particular, to aid Parkinson's patients to suppress hand tremor. In our effort to develop strategies for muscle stimulation control, we first implement a model-based control technique assuming that all the states are measurable. The Hill-type muscle model coupled with a simplified 2DoF model of the arm is used to study the performance of our proposed adaptive sliding mode controller for simulation purpose. However, in the more practical situations, human limb dynamics are extremely complicate and it is inadequate to use model based controllers, especially considering there are still technical limitations that allow in vivo measurements of muscle activity. To tackle these challenges, we have developed output feedback adaptive control approaches for a class of unknown multi-input multi-output systems. Such control strategies are first developed for linear systems, and then extended to the nonlinear case. The proposed controllers, supported by experimental results, require minimum knowledge of the system dynamics and avoid many restrictive assumptions typically found in the literature. Therefore, we expect that the results introduced in this dissertation can provide a solution for a wide class of nonlinear uncertain systems, with focus on practical issues such as partial state measurement and the presence of mismatched uncertainties. / Ph. D.

AN ABSTRACT OF THE THESIS OF PRASHANTHI BANALA, for the Master of Science degree in ELECTRICAL AND COMPUTER ENGINEERING, presented on 31 October 2011, at Southern Illinois University Carbondale. TITLE: OUTPUT FEEDBACK H-inf CONTROL DESIGN FOR MULTI-AGENT SYSTEMS MAJOR PROFESSOR: Dr. Farzad Pourboghrat In this thesis, the design of distributed control for identical multi-agent systems is considered based on the optimization of H-inf cost function. Identical dynamically coupled but interacting systems (agents) are considered where control action of each agent is based on relative output measurement of their neighboring agents and a subset of their own output. The agents communicate with each other to achieve a common goal. A distributed dynamic output feedback control strategy that satisfies H-inf performance for multi-agent systems is developed and corresponding H-inf performance region is analyzed. An example illustrates the necessary and sufficient condition for dynamic output feedback controller synthesis to obtain desired H-inf performance.

Orientador: Edvaldo Assunção / Resumo: Este trabalho aborda o controle via realimentação estática de saída aplicado à sistemas lineares com parâmetro variante (LPV) e lineares incertos invariantes no tempo (LIT). O projeto de ganhos de realimentação estática de saída apresentado neste trabalho é baseado no método dos dois estágios, o qual consiste em primeiramente obter um ganho de realimentação de estados, e então, utilizar esta informação no segundo estágio para obter-se o ganho de realimentação estática de saída desejado. As soluções para os problemas investigados são apresentadas na forma de desigualdades matriciais lineares (no inglês, linear matrix inequalities, LMIs), obtidas por meio da aplicação do Lema de Finsler. Baseado em resultados anteriores encontrados na literatura, este trabalho propõe uma estratégia de relaxação de forma a obter um método menos conservador para obtenção de ganhos robustos de realimentação estática de saída para sistemas incertos LTI. Na estratégia proposta, as variáveis adicionais do Lema de Finsler são consideradas como dependentes de parâmetro, juntamente com o uso de funções de Lyapunov dependentes de parâmetro (no inglês, parameter-dependent Lyapunov functions, PDLFs). É apresentado um estudo avaliando a eficácia da estratégia proposta em fornecer uma maior região de factibilidade para um dado problema. Os resultados foram utilizados em uma comparação com um método de relaxação baseado apenas no uso de PDLFs. Uma segunda contribuição deste trabalho consiste na proposta de um... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The static output feedback (SOF) control applied to linear parameter-varying (LPV) and uncertain linear time-invariant (LTI) systems are addressed in this work. The approach chosen for the design of SOF gains is based on the two-stage method, which consists in obtaining a state feedback gain at first, and then using that information for deriving the desired SOF gain at the second stage. The solutions for the investigated problems are presented in terms of linear matrix inequalities (LMIs), obtained by means of the application of the Finsler's Lemma. Based on previous papers found in literature, this work proposes a relaxation strategy in order to achieve a less conservative method for obtaining robust SOF gains for uncertain LTI systems. In the proposed strategy, the Finsler's Lemma additional variables are considered to be parameter-dependent along with the use of parameter-dependent Lyapunov functions (PDLFs). A study evaluating the effectiveness of the proposed strategy in providing a larger feasibility region for a given problem is presented. The results were used in a comparison with a relaxation method based only on PDLFs. Another contribution of this work lies in the proposal of a solution for the control of LPV systems via the design of a gain-scheduled SOF controller. The methods proposed for both control problems were applied on the design of controllers for an active suspension system. In the experiments, it was assumed that only one of its four system's states wer... (Complete abstract click electronic access below) / Mestre

Estruturas flexíveis estão sujeitas a excitações desconhecidas que podem causar danos. Um dos possíveis artifícios para lidar com este problema é a teoria de controle de sistemas dinâmicos. Em particular, uma técnica que suscita o interessa para aplicação nesta classe de sistemas é o controle ótimo, devido às suas boas propriedades de resposta e factibilidade, podendo ser aplicado até através de circuitos analógicos. O contratempo desta técnica é a necessidade de um número de sensores igual ao número de estados do sistema, o que para estruturas é inviável. Como uma alternativa, pode se empregar os procedimentos usuais de restrição de realimentação do sinal medido. No entanto, estes casos não consideram o projeto das matrizes de saída e entrada, fator determinante para o controle de vibrações em estruturas. O objetivo deste trabalho é preencher esta lacuna. Inicialmente, são introduzidos alguns conceitos das teorias de controle ótimo, dinâmica estrutural e sobre métodos de discretização em séries. Em seguida, determinam-se as condições necessárias de otimalidade considerando como variáveis de otimização o ganho e as posições dos sensores e atuadores. Determinadas as condições, investigam-se os principais desafios para solução destas equações, dados pela existência de parâmetros que estabilizem o sistema e a dependência do ponto ótimo em relação à condição inicial do sistema. O primeiro é resolvido a partir da especificação do sistema linear para uma forma modal e utilizando funções de controle de Lyapunov, o que adicionalmente proporciona o resultado de que o controle colocalizado é um controle ótimo. Para o segundo são propostas duas soluções, sendo uma utilizada para determinar as posições dos atuadores para projetar um controle LQR com desempenho satisfatório, e a outra para determinar os ganhos e posições dos sensores de modo a obter um controle com realimentação de saída com desempenho próximo ao LQR projetado. Os resultados obtidos a partir da aplicação da metodologia desenvolvida em exemplos da dinâmica estrutural revelaram um desempenho notável. Mesmo para uma razão pequena entre o número de sensores pelo número de estados obteve-se um desempenho equivalente ao LQR, exibindo também propriedades robustez consideráveis em relação às variáveis de otimização. Conclui-se que a metodologia desenvolvida é uma boa alternativa para as técnicas de controle LQR e LQG. / Flexible structures are subject to unknown excitations that may cause damage. One of the possible artifices to deal with this problem is the control theory of dynamical systems. In particular, a technique that raises the interest for application in this class of systems is the optimal control, due to its good properties of response and feasibility, as it can be applied even through analog circuits. A drawback of this technique is the need for a number of sensors equal to the number of states, which for structures is impracticable. As an alternative, the usual procedures of using only measured signals for feedback can be employed. However, these cases do not consider the design of the input and output matrices, a determining factor for vibration control in structures. The purpose of this paper is to fill this gap. Initially, some concepts of the theories of optimal control, structural dynamics and series discretization methods are introduced. Then, the optimality conditions are determined considering the gain and locations of sensors and actuators as the optimization variables. Given these conditions, we investigate the main challenges to solve these equations, given by the existence of parameters that stabilize the system and the dependence of the optimum point in relation to the initial condition of the system. The first one is solved from the specification of the linear system to a modal form and using Lyapunov control functions, which additionally provides the result that the collocated control is an optimal control. For the second two solutions are proposed, one being used to determine the positions of the actuators to design a LQR control with satisfactory performance, and the other to determine the gains and positions of the sensors in order to obtain an output feedback control with close performance to the designed LQR. The results obtained from the application of the methodology developed in structural dynamics examples revealed a remarkable performance. Even for a small ratio between the number of sensors by the number of states a performance equivalent to the LQR was obtained, also exhibiting considerable robustness properties in relation to the optimization variables. It is concluded that the developed methodology is a good alternative for LQR and LQG control techniques.

Estruturas flexíveis estão sujeitas a excitações desconhecidas que podem causar danos. Um dos possíveis artifícios para lidar com este problema é a teoria de controle de sistemas dinâmicos. Em particular, uma técnica que suscita o interessa para aplicação nesta classe de sistemas é o controle ótimo, devido às suas boas propriedades de resposta e factibilidade, podendo ser aplicado até através de circuitos analógicos. O contratempo desta técnica é a necessidade de um número de sensores igual ao número de estados do sistema, o que para estruturas é inviável. Como uma alternativa, pode se empregar os procedimentos usuais de restrição de realimentação do sinal medido. No entanto, estes casos não consideram o projeto das matrizes de saída e entrada, fator determinante para o controle de vibrações em estruturas. O objetivo deste trabalho é preencher esta lacuna. Inicialmente, são introduzidos alguns conceitos das teorias de controle ótimo, dinâmica estrutural e sobre métodos de discretização em séries. Em seguida, determinam-se as condições necessárias de otimalidade considerando como variáveis de otimização o ganho e as posições dos sensores e atuadores. Determinadas as condições, investigam-se os principais desafios para solução destas equações, dados pela existência de parâmetros que estabilizem o sistema e a dependência do ponto ótimo em relação à condição inicial do sistema. O primeiro é resolvido a partir da especificação do sistema linear para uma forma modal e utilizando funções de controle de Lyapunov, o que adicionalmente proporciona o resultado de que o controle colocalizado é um controle ótimo. Para o segundo são propostas duas soluções, sendo uma utilizada para determinar as posições dos atuadores para projetar um controle LQR com desempenho satisfatório, e a outra para determinar os ganhos e posições dos sensores de modo a obter um controle com realimentação de saída com desempenho próximo ao LQR projetado. Os resultados obtidos a partir da aplicação da metodologia desenvolvida em exemplos da dinâmica estrutural revelaram um desempenho notável. Mesmo para uma razão pequena entre o número de sensores pelo número de estados obteve-se um desempenho equivalente ao LQR, exibindo também propriedades robustez consideráveis em relação às variáveis de otimização. Conclui-se que a metodologia desenvolvida é uma boa alternativa para as técnicas de controle LQR e LQG. / Flexible structures are subject to unknown excitations that may cause damage. One of the possible artifices to deal with this problem is the control theory of dynamical systems. In particular, a technique that raises the interest for application in this class of systems is the optimal control, due to its good properties of response and feasibility, as it can be applied even through analog circuits. A drawback of this technique is the need for a number of sensors equal to the number of states, which for structures is impracticable. As an alternative, the usual procedures of using only measured signals for feedback can be employed. However, these cases do not consider the design of the input and output matrices, a determining factor for vibration control in structures. The purpose of this paper is to fill this gap. Initially, some concepts of the theories of optimal control, structural dynamics and series discretization methods are introduced. Then, the optimality conditions are determined considering the gain and locations of sensors and actuators as the optimization variables. Given these conditions, we investigate the main challenges to solve these equations, given by the existence of parameters that stabilize the system and the dependence of the optimum point in relation to the initial condition of the system. The first one is solved from the specification of the linear system to a modal form and using Lyapunov control functions, which additionally provides the result that the collocated control is an optimal control. For the second two solutions are proposed, one being used to determine the positions of the actuators to design a LQR control with satisfactory performance, and the other to determine the gains and positions of the sensors in order to obtain an output feedback control with close performance to the designed LQR. The results obtained from the application of the methodology developed in structural dynamics examples revealed a remarkable performance. Even for a small ratio between the number of sensors by the number of states a performance equivalent to the LQR was obtained, also exhibiting considerable robustness properties in relation to the optimization variables. It is concluded that the developed methodology is a good alternative for LQR and LQG control techniques.

<p>This thesis considers the problem of fault diagnosis and fault-tolerant control (FTC) for chemical process systems with nonlinear dynamics. The primary objective of fault diagnosis discussed in this work is to identify the failed actuator or sensor by using the information embodied in a process model, as well as input and output data. To this end, an active fault isolation method is first proposed to identify actuator faults and process disturbances by utilizing control action and process nonlinearity. The key idea is to move the process to a region upon fault detection where the effect of each fault can be differentiated from others. The proposed method enables isolation of faults that may not be achievable under nominal operation. This work then investigates the problem of sensor fault isolation by exploiting model-based sensor redundancy through state observer design. Specifically, a high-gain observer is presented and the stability property of the closed-loop system is rigorously established. A method that uses a bank of high-gain observers is then proposed to isolate sensor faults, which explicitly accounts for process nonlinearity, and to continue nominal operation upon fault isolation. In addition to fault diagnosis, this work addresses the problem of handling severe actuator faults using a safe-parking approach and integrating fault diagnosis and safe-parking techniques in a unified fault-handling framework. In particular, several practical issues are considered for the design and implementation of safe-parking techniques, including changes in process dynamics, the network structure of a chemical plant, and actuators frozen at arbitrary positions. The advantage of this approach is that it enables stable process operation under faulty conditions, avoiding the partial or entire shutdown of a chemical plant and resulting economic losses. The efficacy of the proposed fault diagnosis and FTC methods is demonstrated through numerous simulations of chemical process examples.</p> / Doctor of Philosophy (PhD)