A thorough review of the literature on the model reduction of linear, time-invariant, dynamical systems in both the frequency and time domains is presented. Particular attention is paid to the least-squares extension of the classical method of Padé approximation. An account is given of the development of apparently different approaches of least-squares parameter- matching Padé model reduction applied to continuous-time and discrete-time systems. These approaches are shown to be related via a unifying theory. From the formulation it is possible to show several interesting features of the least-squares approach which lead to a fuller understanding of exactly how the reduced model approximates the full system. An error index is derived in the general continuous-time case and it is shown that a range of system parameter preservation options are available. Using the theory developed in the continuous-time case a non-uniqueness property of the method is proven. An ‘optimal’ least-squares method based on the approach and the introduction of weighting for the system parameters are both investigated. The unifying theory is extended to the discrete-time case where an important new stability preservation property is proved and is shown to provide the basis for a new least- squares Padé method. This method uses transformations between the z- and 5-planes to guarantee stable reduced order models approximating stable high order continuous-time systems. The application of least-squares Padé approximation is further extended to the multivariable case with particular attention given to the factors affecting the levels of order reduction achieved. Appropriate numerical examples are used to illustrate the main points of the thesis and graphs of the impulse and step responses are used throughout to visually highlight the accuracy of approximation.

Orientador: José Paulo Fernandes Garcia / Banca: Haroldo Rodrigues de Azevedo / Banca: Marcelo Carvalho M. Teixeira / Resumo: Este trabalho apresenta uma nova estratégia de controle discreto. A técnica é baseada em Modos Deslizantes Discretos, utilizando uma lei de controle suave. Quando um algoritmo de controle é implementado em um computador digital, existe um atraso no tempo de computação, devido ao tempo de execução das instruções. Neste trabalho, vamos assumir que estes atrasos são constantes e menores que um período de amostragem. A presença do atraso no tempo de computação não apenas reduz a estabilidade e robustez, mas também degrada a performance de controle. O novo controlador proposto é projetado para atuar na presença destes atrasos, melhorando substancialmente o desempenho do controle. Outra propriedade importante deste controlador é a possibilidade de trabalhar com períodos de amostragem mais altos, garantindo o uso de freqüências mais baixas de processamento, ou seja, proporcionando uma economia do hardware de atuação. A nova lei de controle proposta foi aplicada na estabilização de quatro sistemas incertos e de natureza instável: Sistema Bola e Viga, Sistema Pêndulo Invertido Linear, Sistema Pêndulo Invertido Rotacional e Sistema Pêndulo Invertido Rotacional Duplo. Resultados das simulações são apresentados e comparados com resultados de outro controlador de Modo Deslizante, proposto na literatura, caracterizando um estudo comparativo, onde a eficácia do novo controlador projetado se mostra evidente, devido a seu algoritmo de fácil elaboração prática. Para melhor visualização do comportamento dos sistemas estudados e visando a contribuição no aprendizado de sistemas de controle, modelos de animação em três dimensões foram utilizados. / Abstract: This work presents a new strategy of discrete-time control. The technique is based on Discrete-Time Sliding Modes, using a smooth control law. When a control algorithm is implemented in a digital computer, there is a computation time delay, due the execution time of the instructions. In this work, we go to assume that these delays are constant and smaller than a sampling period. The presence of the computation time delay not only reduces the stability and robustness, but also degrades the control performance. The new considered controller is projected to work in the presence of these delays, improving substantially the performance of the control. Another important property of this controller is the possibility to work with higher sampling periods, guaranteeing the use of lower frequencies of processing, providing an economy of the actuation hardware. The new control law proposal was applied in the stabilization of four uncertain systems with unstable nature: Ball and Beam System, Linear Inverted Pendulum System, Rotational Inverted Pendulum System and Double Rotational Inverted Pendulum System. Simulations results are presented and compared with results of other Sliding Mode controller, proposed in the literature, characterizing a comparative study, where the effectiveness of the new designed controller shows evident, due your algorithm of easy practical elaboration. For better visualization of the behavior of the systems studied and aiming at the contribution in the learning of control systems, models of animation in three dimensions had been used. / Mestre

Please read the abstract in the front section of this document / Dissertation (MSc (Mathematics))--University of Pretoria, 2005. / Mathematics and Applied Mathematics / unrestricted

Feedback is used to control systems whose open-loop behaviour is uncertain. Over the last twenty years a mature theory of robust control has been developed for linear multivariable systems in continuous time. But most practical control systems have constraints such as saturation limits on the actuators, which render the closed-loop nonlinear. Most of the modern controllers are also implemented digitally using computers.The study of this research is divided in two directions: the stability analysis of discrete-time Lur’e systems and the synthesis of static discrete-time anti-windup schemes. With respect to stability analysis, the main contributions of this thesis are the derivations of new LMI-based stability criteria for the discrete-time Lur’e systems with monotonic, slope-restricted nonlinearities via the Lyapunov method. The criteria provide convex stability conditions via LMIs, which can be efficiently computed via convex optimization methods. They are also extended to the general case that includes the non-diagonal MIMO nonlinearities. The importance of extending them to the general case is that it can eventually be applied to the stability analysis of several optimization-based controllers such as an input-constrainedmodel predictive control (MPC), which is inherently discrete. With respect to synthesis, the contribution is the convex formulation of a static discrete-time anti-windup scheme via one of the Jury-Lee criteria (a discrete-time counterpart of Popov criterion), which was previously conjectured to be unachievable. The result is also in the form of LMI, and is extended to several existing static anti-windup schemes with open-loop stable plants.

A new approach to the identification problem of linear continuous-time time-invariant systems from input-output measurements is presented. Both parametric and nonparametric system models are considered. The new approach is based on the use of continuous-time functions, the modal functions, defined in terms of the system output, the output derivatives and the state variables under the assumption that the order n of the observable system is known a priori. The modal functions are obtained by linear filtering operations of the system output, the output derivatives and the state variables so that the modal functions are independent of the system instantaneous state. In this case, the modal functions are linear functions of the input exponential modes, and they contain none of the system exponential modes unlike the system general response which contains modes from both the system and the input. The filters parameters, the modal parameters are estimated using linear regression techniques. The modal functions and the modal parameters of the output and its derivatives are used to identify parametric input-output and state models of the system. The coefficients of the system characteristic polynomial are obtained by solving n algebraic equations formed from the estimates of the modal parameters. Estimates of the parameters associated with the system zeros are obtained by solving another set of linear algebraic equation. The system frequency response and step response are estimated using the output modal function. The impulse response is obtained by filtering the estimated step response using the output first derivative modal parameters. A new method is presented to obtain the system poles as the eigenvalues of a data matrix formed from the system free response. The coefficients of the system characteristic polynomial are obtained from the data matrix through a simple recursive equation. This method has some important advantages over the well known Prony's method. The state modal functions are used to obtain a minimum-time observer that gives the continuous-time system state as a direct function of input-output samples in n sampling intervals. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

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Discrete-time survival analysis as an educational research technique has focused on analysing and interpretating parameter estimates. The purpose of this study was to examine the effects of certain data characteristics on the hazard estimates and goodness of fit statistics. Fifty-four simulated data sets were crossed with four conditions in a 2 (time period) by 3 (distribution of Y = 1) by 3 (distribution of Y = 0) by 3 (sample size) design.