Sensorless control of the synchronous reluctance motor has been a topic of research for more than a decade, producing several successful methods to accomplish this goal. However, a technique that has been overlooked is the full-order nonlinear observer, which is essentially a software model of the motor driven by measurements from the actual motor. Presented in this thesis is the design, implementation, and experimental testing of a full-order observer-based sensorless control technique which requires only the phase current and voltage measurements that are typically available in standard three-phase inverters. A technique is also presented for calculating a table of observer feedback gains parameterized only by the steady-state motor speed. This allows a gain-scheduling observer to be implemented which, as shown using experiments, improves the transient response of the observer over a wide speed range. The sensorless controller consists of a full-order nonlinear observer coupled with an input-output linearization speed controller. The resulting controller was implemented in Simulink and executed on a dSPACE DS1103 real-time DSP board using the Real-Time Workshop extension to Simulink. A custom built three-phase IGBT inverter was used to interface the DSP to a 100 watt synchronous reluctance motor for laboratory testing. The resulting sensorless controller was able to successfully track a varying speed reference from 150 rpm to 1800 rpm with a tracking error under 5% for most of the speed range. At the lowest speeds, the tracking error begins to increase but the observer remains stable down to 150 rpm.

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In the chemical or biochemical industry most processes are modeled by nonlinear equations. It is of a great significance to design high-performance nonlinear controllers for efficient control of these nonlinear processes to achieve closed-loop system's stability and high performance. However, there are many difficulties which hinder the design of such controllers due mainly to the process nonlinearity. In this work, comprehensive design procedures based on robust control have been proposed to efficiently deal with the design of gain-scheduled controllers for nonlinear systems. Since all the design procedures proposed in this work rely strongly on the process model, the first difficulty addressed in this thesis is the identification of a relatively simple model of the nonlinear processes under study. The nonlinearity of the processes makes it often difficult to obtain a first-principles model which can be used for analysis and design of the controller. As a result, relatively simple empirical models, Volterra series model and state-affine model, are chosen in this work to represent the nonlinear process for the design of controllers. The second major difficulty is that although the nonlinear models used in this thesis are easy to identify, the analysis of stability and performance for such models using nonlinear control theory is not straightforward. Instead, it is proposed in this study to investigate the stability and performance using a robust control approach. In this approach, the nonlinear model is approximated by a nominal linear model combined with a mathematical description of model error to be referred to, in this work, as model uncertainty. In the current work it was assumed that the main source of uncertainty with respect to the nominal linear model is due to the system nonlinearity. Then, in this study, robust control theoretical tools have been especially developed and applied for the design of gain-scheduled Proportional-Integral (PI) control and gain-scheduled Model Predictive Control (MPC). Gain-scheduled controllers are chosen because for nonlinear processes operated over a wide range of operation, gain-scheduling has proven to be a successful control design technique (Bequette, 1997) for nonlinear processes. To guarantee the closed-loop system's robust stability and performance with the designed controllers, a systematic approach has been proposed for the design of robust gain-scheduled controllers for nonlinear processes. The design procedure is based on robust stability and performance conditions proposed in this work. For time-varying uncertain parameters, robust stability and performance conditions using fixed Lyapunov functions and parameter-dependent Lyapunov functions, were used. Then, comprehensive procedures for the design and optimization of robust gain-scheduled PI and MPC controllers tuning parameters based on the robust stability and performance tests are then proposed. Since the closed-loop system represented by the combination of a state-affine process model and the gain-scheduled controller is found to have an affine dependence on the uncertain parameters, robust stability and performance conditions can be tested by a finite number of Linear Matrix Inequalities (LMIs). Thus, the final problems are numerically solvable. One of the inherent problems with robust control is that the design is conservative. Two approaches have been proposed in this work to reduce the conservatism. The first one is based on parameter-dependent Lyapunov functions, and it is applied when the rate of change of the time-varying uncertainty parameters is <i>a priori</i> available. The second one is based on the relaxation of an input-saturation factor defined in the thesis to deal with the issue of actuator saturation. Finally, to illustrate the techniques discussed in the thesis, robust gain-scheduled PI and MPC controllers are designed for a continuous stirred tank reactor (CSTR) process. A simple MIMO example with two inputs and two outputs controlled by a multivariable gain-scheduled MPC controller is also discussed to illustrate the applicability of the methods to multivariable situations. All the designed controllers are simulated and the simulations show that the proposed design procedures are efficient in designing and comparing robust gain-scheduled controllers for nonlinear processes.

In the chemical or biochemical industry most processes are modeled by nonlinear equations. It is of a great significance to design high-performance nonlinear controllers for efficient control of these nonlinear processes to achieve closed-loop system's stability and high performance. However, there are many difficulties which hinder the design of such controllers due mainly to the process nonlinearity. In this work, comprehensive design procedures based on robust control have been proposed to efficiently deal with the design of gain-scheduled controllers for nonlinear systems. Since all the design procedures proposed in this work rely strongly on the process model, the first difficulty addressed in this thesis is the identification of a relatively simple model of the nonlinear processes under study. The nonlinearity of the processes makes it often difficult to obtain a first-principles model which can be used for analysis and design of the controller. As a result, relatively simple empirical models, Volterra series model and state-affine model, are chosen in this work to represent the nonlinear process for the design of controllers. The second major difficulty is that although the nonlinear models used in this thesis are easy to identify, the analysis of stability and performance for such models using nonlinear control theory is not straightforward. Instead, it is proposed in this study to investigate the stability and performance using a robust control approach. In this approach, the nonlinear model is approximated by a nominal linear model combined with a mathematical description of model error to be referred to, in this work, as model uncertainty. In the current work it was assumed that the main source of uncertainty with respect to the nominal linear model is due to the system nonlinearity. Then, in this study, robust control theoretical tools have been especially developed and applied for the design of gain-scheduled Proportional-Integral (PI) control and gain-scheduled Model Predictive Control (MPC). Gain-scheduled controllers are chosen because for nonlinear processes operated over a wide range of operation, gain-scheduling has proven to be a successful control design technique (Bequette, 1997) for nonlinear processes. To guarantee the closed-loop system's robust stability and performance with the designed controllers, a systematic approach has been proposed for the design of robust gain-scheduled controllers for nonlinear processes. The design procedure is based on robust stability and performance conditions proposed in this work. For time-varying uncertain parameters, robust stability and performance conditions using fixed Lyapunov functions and parameter-dependent Lyapunov functions, were used. Then, comprehensive procedures for the design and optimization of robust gain-scheduled PI and MPC controllers tuning parameters based on the robust stability and performance tests are then proposed. Since the closed-loop system represented by the combination of a state-affine process model and the gain-scheduled controller is found to have an affine dependence on the uncertain parameters, robust stability and performance conditions can be tested by a finite number of Linear Matrix Inequalities (LMIs). Thus, the final problems are numerically solvable. One of the inherent problems with robust control is that the design is conservative. Two approaches have been proposed in this work to reduce the conservatism. The first one is based on parameter-dependent Lyapunov functions, and it is applied when the rate of change of the time-varying uncertainty parameters is <i>a priori</i> available. The second one is based on the relaxation of an input-saturation factor defined in the thesis to deal with the issue of actuator saturation. Finally, to illustrate the techniques discussed in the thesis, robust gain-scheduled PI and MPC controllers are designed for a continuous stirred tank reactor (CSTR) process. A simple MIMO example with two inputs and two outputs controlled by a multivariable gain-scheduled MPC controller is also discussed to illustrate the applicability of the methods to multivariable situations. All the designed controllers are simulated and the simulations show that the proposed design procedures are efficient in designing and comparing robust gain-scheduled controllers for nonlinear processes.

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No description available.

Este trabalho apresenta todo um projeto de um sistema de supervisão e controle de um trocador de calor, desde os ensaios experimentais para a elaboração de um modelo matemático até a implementação do sistema de controle e supervisão em microcomputador. O sistema implementado consiste de um software didático e um sistema de aquisição de dados que irão realizar a supervisão e controle de um trocador de calor tipo casco e tubos. Neste software didático é possível implementar o controle PID e suas variações PI-D e I-PD além de permitir a implementação do sistema de controle adaptativo estrutura gain scheduling o qual muda os parâmetros de um controle PID de acordo com a mudança da dinâmica do trocador de calor. Como o trocador de calor apresenta um tempo morto em sua dinâmica, então optou-se por adicionar ao software didático um controle com algoritmo preditivo estrutura Preditor de Smith desta forma é possível realizar ensaios com e sem o algoritmo preditivo para uma comparação de resultados. Este sistema de supervisão e controle do trocador de calor poderá ser usado como ferramenta didática para alunos de diversos cursos, onde é possível realizar ensaios de diferentes estruturas de controle para posterior comparação e estudo de seus resultados. Resultados práticos de todas as estruturas de controle que o software implementa são apresentados e comparados neste trabalho. / This work presents thorough a supervision and control system project of a heat exchanger, from the experimental tests for the mathematical model rising to the control system implementation and supervision in a microcomputer. The implemented system consists of didactic software and a data acquisition system that will perform the supervision and control of a heat exchanger shell and tube type. In this didactic software it is possible to implement the PID control and its variations PI-D and I-PD besides allowing the implementation of the adaptive control system gain scheduling structure, which changes the PID control parameters according to the changes of the heat exchanger dynamics. As the heat exchanger presents dead time on its dynamics, it was opted to add to the didactic software a control with Smith Predictor structure predictive algorithm, thus it is possible to perform tests with and without the predictive algorithm for result comparison. This supervision and control system of the heat exchanger will be able to be used as a didactic tool for students from several courses, where it is possible to perform tests with different control structures to further comparison and study of its results. Pratical results of all the control structures that the software implements are presented and compared in this work.

Este trabalho apresenta todo um projeto de um sistema de supervisão e controle de um trocador de calor, desde os ensaios experimentais para a elaboração de um modelo matemático até a implementação do sistema de controle e supervisão em microcomputador. O sistema implementado consiste de um software didático e um sistema de aquisição de dados que irão realizar a supervisão e controle de um trocador de calor tipo casco e tubos. Neste software didático é possível implementar o controle PID e suas variações PI-D e I-PD além de permitir a implementação do sistema de controle adaptativo estrutura gain scheduling o qual muda os parâmetros de um controle PID de acordo com a mudança da dinâmica do trocador de calor. Como o trocador de calor apresenta um tempo morto em sua dinâmica, então optou-se por adicionar ao software didático um controle com algoritmo preditivo estrutura Preditor de Smith desta forma é possível realizar ensaios com e sem o algoritmo preditivo para uma comparação de resultados. Este sistema de supervisão e controle do trocador de calor poderá ser usado como ferramenta didática para alunos de diversos cursos, onde é possível realizar ensaios de diferentes estruturas de controle para posterior comparação e estudo de seus resultados. Resultados práticos de todas as estruturas de controle que o software implementa são apresentados e comparados neste trabalho. / This work presents thorough a supervision and control system project of a heat exchanger, from the experimental tests for the mathematical model rising to the control system implementation and supervision in a microcomputer. The implemented system consists of didactic software and a data acquisition system that will perform the supervision and control of a heat exchanger shell and tube type. In this didactic software it is possible to implement the PID control and its variations PI-D and I-PD besides allowing the implementation of the adaptive control system gain scheduling structure, which changes the PID control parameters according to the changes of the heat exchanger dynamics. As the heat exchanger presents dead time on its dynamics, it was opted to add to the didactic software a control with Smith Predictor structure predictive algorithm, thus it is possible to perform tests with and without the predictive algorithm for result comparison. This supervision and control system of the heat exchanger will be able to be used as a didactic tool for students from several courses, where it is possible to perform tests with different control structures to further comparison and study of its results. Pratical results of all the control structures that the software implements are presented and compared in this work.

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

Orientador: Edvaldo Assunção / Resumo: Neste trabalho são propostos resultados para a estabilidade de sistemas lineares sujeitos a parâmetros variantes no tempo (do inglês, Linear Parameter Varying - LPV) e incertezas paramétricas. De início, apresenta-se um método para o projeto de um controlador robusto e gain scheduled via desigualdades matriciais lineares (do inglês, Linear Matrix Inequalitities - LMIs), com base na teoria de estabilidade segundo Lyapunov, com parâmetro variante no tempo e empregando a realimentação derivativa. Propõe-se um método para projetar o controlador gain scheduled usando realimentação derivativa, considerando também incertezas paramétricas. Esta nova formulação foi obtida utilizando o Lema de Finsler, o que permitiu determinar o ganho do controlador sem a necessidade de inverter uma matriz literal. Condições menos conservadoras foram projetadas para um controlador gain scheduled considerando a realimentação dos estados do sistemas. Simulações computacionais com exemplos numéricos mostram que os teoremas propostos neste trabalho são menos conservadores do que os existentes na literatura. A metodologia apresentada foi implementada no sistema de suspensão ativa. / Abstract: In this work, results for the stability of linear parameter-varying (LPV) systems and parametric uncertainties are poposed. At first, a method for desining a gain scheduled and robust controller is described via linear matrix inequalities (Linear Matrix Inequalitities - LMIs), based on the stability theory of Lyapunov, with time-variant parameters and using state derivative feedback. A method to design a gain scheduling controller using state derivative feedback and also considering parametric uncertains is proposed. This new formulation was manipulated using the Finsler’s Lemma, and allowed to determine the control law without having to invert a symbolic matrix. Less conservative conditions were designed for a gain scheduled controller considering system state feedback. Computational simulations with numerical examples show that the theorems proposed in this work are less conservative than those in the literature. The presented methodology was implemented in the active suspension system. / Doutor