Modern control design is sometimes accompanied by the challenge of dealing with nonlinear systems or plants. In some situations, due to the complexity of the plant and the unavailability of suitable models, the controls engineer opts for developing control schemes based on look-up tables. These tables, typically populated with the steady state inverse input-output characteristics of the plant, are used to compensate the plant via open-loop or closed-loop to solve the control problem. In an effort to present a new alternative, a general theoretical framework for online auto-calibration and control of general nonlinear systems is developed in this dissertation. This technique simultaneously learns the inverse input-state mapping (i.e. the calibration mapping) of the plant while forcing its state to follow a prescribed desired trajectory. The main requirements for the successful application of the novel control law are knowledge of the order of the plant and some generic data to initialize the inverse mapping. This last requirement can be easily fulfilled by using steady-state data or the equilibrium points of the plant. In this approach, the inverse mapping is learned from the current and past states. The learning is accomplished in a composite manner by employing input and state errors. The map is used simultaneously in the feedforward path to control the plant. The performance of the plant subject to this novel controller is validated through simulations and experimental data. The new control method is applied to a novel Electro-Hydraulic Poppet Valve (EHPV). These valves are used in a Wheatstone bridge arrangement for motion control of hydraulic actuators. This is preferred over the conventional use of spool valves due to the energy savings potential. It is shown in this dissertation that this method improves the value of using these types of valves for motion control in hydraulics. This is due to the combination of self-learning (auto-calibration) and better performance for a more efficient operation of hydraulic equipment. Additionally, it is shown that the auto-calibration of the valves can be used for health monitoring of the same, which consequently improves their reliability and expedites maintenance downtime.

Thesis (Ph.D.)--Mississippi State University. Department of Physics and Astronomy. / Title from title screen. Includes bibliographical references.

This thesis investigates the frequency weighted balanced model reduction problem for linear time invariant systems. Both continuous and discrete time systems are considered, in one and two-dimensions. First the frequency weighted balanced model reduction problem is formulated, then a novel frequency weighted, balanced, model reduction method for continuous time systems is proposed. This method is based on the retention of frequency weighted Hankel singular values of the original system, and yields stable reduced order models even when two sided weightings are employed. An alternative frequency weighted balanced model reduction technique (applicable for controller reduction applications) is then developed. This is based on a parametrized combination of the frequency weighted partial fraction expansion technique with balanced truncation and the singular perturbation approximation techniques. This method yields stable models even when two sided weightings are employed. An a priori error bound for the model reduction method is derived. Lower frequency response errors and error bounds are obtained using free parameters and equivalent anti-stable weightings. Based on the same idea, a novel parameterized frequency weighted optimal Hankel norm model reduction method with a tighter a priori error bound is proposed. The proposed methods are extended to include discrete time systems. A frequency interval Gramians based stability preserving model reduction scheme with error bounds is also presented. In this case, frequency weights are not explicitly predefined. Discrete time system related results are also included. Several frequency weighted model reduction results for two-dimensional (2-D) systems are also proposed. The advantages of these schemes include error bounds, guaranteed stability and applicability to general stable (non-separable denominator) weighting functions. Finally, a novel 2-D identification based frequency weighted model reduction scheme is outlined. Numerically robust algorithms based on square root and balancing free techniques are proposed for frequency weighted balanced truncation techniques. Several practical examples are included to illustrate the effectiveness of the algorithms.

Este trabalho apresenta uma proposta de um software de simulação e diagnóstico de falhas aplicado a um sistema de automação. para realizar esta tarefa foi desenvolvido um estudo de caso que contem um problema de automação industrial. Deste estudo foi retirado um modelo, usado como base para criar do software de simulação que segue as especificações dos modelos, no qual é possível observar a evolução dos eventos através de sua linguagem e diagnosticar falhas, quando estas ocorrem em uma das máquinas da planta. O processo de diagnóstico de falhas tem como base as regras de diagnosticabilidade apresentadas na literatura. As máquinas, assim como suas restrições, são modeladas dentro do próprio software, onde são definidas as estruturas de cada automato assim como características como observabilidade, controlabilidade e a possibilidade de falhar. Os testes realizados no sistema apresentado mostraram que a linguagem de controle consegue, mesmo permitindo um nivel de liberdade ao sistema, identificar as falhas verificando somente para os eventos que ocorrem após a ocorrência da mesma. / This work we presents a proposal a software of simulation and fault diagnosis applied to an automation system. In that task was developed , a case study that contains a problem of industrial automation. The study was used as the source for creating the simulation that follows the specifications of software models, where you can observe the evolution of events through its language and diagnose faults when they occur in one of the machines of the plant. The process of fault diagnosis is based on the rules of diagnosticabilidades presented in the literature. The machines, as well as its restrictions are modeled within the software itself, where the structures of each automaton are defined the caracteristics as observability an the possibility of failure. The tests in the system showed that of the language used can allowing identify fails, checking only for events that occorem after the occurence the fails.

Este trabalho apresenta uma proposta de um software de simulação e diagnóstico de falhas aplicado a um sistema de automação. para realizar esta tarefa foi desenvolvido um estudo de caso que contem um problema de automação industrial. Deste estudo foi retirado um modelo, usado como base para criar do software de simulação que segue as especificações dos modelos, no qual é possível observar a evolução dos eventos através de sua linguagem e diagnosticar falhas, quando estas ocorrem em uma das máquinas da planta. O processo de diagnóstico de falhas tem como base as regras de diagnosticabilidade apresentadas na literatura. As máquinas, assim como suas restrições, são modeladas dentro do próprio software, onde são definidas as estruturas de cada automato assim como características como observabilidade, controlabilidade e a possibilidade de falhar. Os testes realizados no sistema apresentado mostraram que a linguagem de controle consegue, mesmo permitindo um nivel de liberdade ao sistema, identificar as falhas verificando somente para os eventos que ocorrem após a ocorrência da mesma. / This work we presents a proposal a software of simulation and fault diagnosis applied to an automation system. In that task was developed , a case study that contains a problem of industrial automation. The study was used as the source for creating the simulation that follows the specifications of software models, where you can observe the evolution of events through its language and diagnose faults when they occur in one of the machines of the plant. The process of fault diagnosis is based on the rules of diagnosticabilidades presented in the literature. The machines, as well as its restrictions are modeled within the software itself, where the structures of each automaton are defined the caracteristics as observability an the possibility of failure. The tests in the system showed that of the language used can allowing identify fails, checking only for events that occorem after the occurence the fails.

Esta tese trata do problema de controle ótimo estocástico de sistemas com saltos Markovianos e ruído multiplicativo a tempo discreto, com horizontes de tempo finito e infinito. A função custo é composta de termos quadráticos e lineares nas variáveis de estado e de controle, com matrizes peso indefinidas. Como resultado principal do problema com horizonte finito, é apresentada uma condição necessária e suficiente para que o problema de controle seja bem posto, a partir da qual uma solução ótima é derivada. A condição e a lei de controle são escritas em termos de um conjunto acoplado de equações de Riccati interconectadas a um conjunto acoplado de equações lineares recursivas. Para o caso de horizonte infinito, são apresentadas as soluções ótimas para os problemas de custo médio a longo prazo e com desconto, derivadas a partir de uma solução estabilizante de um conjunto de equações algébricas de Riccati acopladas generalizadas (GCARE). A existência da solução estabilizante é uma condição suficiente para que tais problemas sejam do tipo bem posto. Além disso, são apresentadas condições para a existência das soluções maximal e estabilizante do sistema GCARE. Como aplicações dos resultados obtidos, são apresentadas as soluções de um problema de otimização de carteiras de investimento com benchmark e de um problema de gestão de ativos e passivos de fundos de pensão do tipo benefício definido, ambos os casos com mudanças de regime nas variáreis de mercado. / This thesis considers the finite-horizon and infinite-horizon stochastic optimal control problem for discrete-time Markov jump with multiplicative noise linear systems. The performance criterion is assumed to be formed by a linear combination of a quadratic part and a linear part in the state and control variables. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. For the finite-horizon problem the main results consist of deriving a necessary and sufficient condition under which the problem is well posed and a optimal control law is derived. This condition and the optimal control law are written in terms of a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. For the infinite-horizon problem a set of generalized coupled algebraic Riccati equations (GCARE) is studied. In this case, a sufficient condition under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution for the GCARE are presented. Moreover, a solution for the discounted and long run average cost problems is presented. The results obtained are applied to solver a portfolio optimization problem with benchmark and a pension fund problem with regime switching.

Orientador: Jose Claudio Geromel / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-10T01:06:21Z (GMT). No. of bitstreams: 1 Fioravanti_AndreRicardo_M.pdf: 793181 bytes, checksum: 6f60b78faabe194cc22f2cc3157f0d90 (MD5) Previous issue date: 2007 / Resumo: Esta dissertação tem par principal objetivo o estudo do problema de projeto de filtros H2 e Hoo de sistemas lineares discretos com parâmetros sujeitos a saltos markovianos. Inicialmente, sob a hipótese de que o parâmetro da cadeia de Markov é mensurável, fornecemos a caracterização de todos os filtros tais que o erro de estimação é limitado por uma norma, produzindo a solução completa do problema de projeto dependente do modo da cadeia. Baseado neste resultado, consideramos o projeto do filtro robusto capaz de lidar com incertezas paramétricas. Em seguida, propomos um procedimento de projeto de filtros sem o conhecimento da cadeia. Todos os problemas de filtragem são expressos em termos de desigualdades matriciais lineares. Os resultados teóricos são ilustrados através de uma aplicação prática que consiste na comunicação de dados através de um canal markoviano / Abstract: This thesis addresses the H2 and Hoo filtering design problem of discrete-time Markov jump linear systems. First, under the assumption that the Markov parameter is measurable, we provide the characterization of all filters such that the estimation errar remains bounded by a given narm leveI, yielding the complete solution of the mode-dependent filtering design problem. Based on this result, a robust filter design to deal with convex bounded parameter uncertainty is considered. In the sequeI, a design procedure for modeindependent filtering design is proposed. All filters are designed by solving linear matrix inequalities. The theory is illustrated by means of a practical example, consisting the data communication through a markovian channel / Mestrado / Automação / Mestre em Engenharia Elétrica

Le travail présenté dans cette thèse s'inscrit dans le cadre de l'étude de l'efficacité de la commande CRONE avec effet anticipatif robuste dans les problèmes de poursuite et de régulation pour les systèmes monovariables et multivariables. L'objectif de l'anticipation est de concevoir des algorithmes de commande capables de minimiser un critère quadratique basé sur l'erreur entre la sortie du système et le signal de référence avec modération du niveau du signal de commande. La solution proposée repose sur l'association d'une commande robuste de type feedback à une commande anticipative de type feedforward. L'action feedforward utilise un filtre anticipatif synthétisé dans le domaine fréquentiel en utilisant des critères d'optimalité et de contraintes de type $mathcal{H}_2$ et $mathcal{H}_infty$. La réduction du nombre de paramètres du filtre anticipatif en utilisant une période d'échantillonnage plus lente a été traitée. Des exemples académiques illustrent les développements théoriques. Une application pratique sur un système de régulation hydraulique a montré la pertinence de cette nouvelle approche. / The work presented in this thesis is part of the study of the effectiveness of CRONE control with anticipative effect in the problems of tracking and control for monovariable and multivariable systems. The anticipation objective is to design a control algorithm that minimizes a quadratic error between the reference and the output of the system and at the same time achieve a good level of the control signal. The proposed solution combines a robust feedback control with a feedforward control. The feedforward action uses optimality criteria and an anticipative filter which is designed in the frequency domain using a mix of $mathcal{H}_2$ et $mathcal{H}_infty$ constraints. The reduction of the number of parameters of the anticipative filter by using a slower sampling period for the anticipative filter is treated. Academic examples highlight the theoretical developments. A practical application on a hydraulic control system has shown the efficiency of the developed approach.

Nesta tese de doutorado são apresentados sistemas globais de estimativa baseados em modelos Markovianos aplicados na área de reabilitação robótica. Os sistemas propostos foram desenvolvidos para estimar as posições angulares dos elos de exoesqueletos para membros inferiores, desenvolvidos para reabilitação motora em pacientes que sofreram Acidente Vascular Cerebral (AVC) ou lesão medular. Filtros baseados no filtro de Kalman, um nominal e outro considerando incertezas no modelo, foram utilizados em estratégias de fusão de dados de sensores provenientes de sensores inerciais, possibilitando estimativas de posicionamentos angulares. Algoritmos genéticos são utilizados na otimização dos filtros, ajustando as matrizes de peso destes. Em oposição as modelagens tradicionais, via estimativa local, utilizando somente uma unidade inercial para cada modelo, propõe-se um sistema global de estimativa, obtendo-se a melhor informação de cada sensor combinando-os em um modelo Markoviano. Resultados experimentais com um exoesqueleto foram utilizados para comparar a abordagem Markoviana às convencionais. / In this thesis are presented global estimation systems based on Markov models applied in robotic rehabilitation area. The proposed systems have been developed to estimate the angular positions of the exoskeletons for lower limbs, designed to provide motor rehabilitation of stroke and spinal cord injured people. Filters based on the Kalman filter, one nominal and other considering uncertainties in the model, were used in sensor data fusion strategies from inertial sensors, to estimate angular positions. Genetic algorithms are used to the optimization of filters, tuning the weighting matrices. In opposition to these modelling via local estimation, using only one inertial unit, we also chose a global modelling getting the best information from each sensor, combining them in a Markov model. Experimental results with an exoskeleton were used to compare the Markovian approach to conventional.

Esta dissertação de mestrado aborda o problema de regulação robusta recursiva para sistemas lineares discretos sujeitos a incertezas paramétricas. Um novo funcional quadrático, baseado na combinação de função penalidade e função custo do tipo jogos, é projetado para lidar com este problema. Uma característica interessante desta abordagem é que a recursividade pode ser realizada sem a necessidade do ajuste de parâmetros auxiliares. Bastante útil para aplicações online. A solução proposta é baseada numa equação recursiva de Riccati. Também, a convergência e a estabilidade do regulador para o sistema linear incerto invariante no tempo são garantidas. / This dissertation deals with robust recursive regulators for discrete-time systems subject to parametric uncertainties. A new quadratic functional based on the combination of penalty functions and game theory is proposed to solve this class of problems. An important issue of this approach is that the recursiveness can be performed without the need of adjusting auxiliary parameters. It is useful for online applications. The solution proposed is based on Riccati equation which guarantees the convergence and stability of the time-invariant system.