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The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output systems are introduced, and the class of systems considered is defined. It is noted that the stochastic tracking problem divides into a deterministic tracking problem and a stochastic regulator problem; the solutions to these two problems are shown to be independent but formally similar. The continuous regulator problem is approached via both frequency and time domain methods: the former method is extended to cover unstable systems; the latter method is extended to include systems with input delay. The two regulators are shown to be externally equivalent. The frequency domain method is briefly described for discrete systems, and shown to include the minimum variance regulator of Åström and Peterka as a special case. Some systems which allow measurement noise to be treated as a system disturbance for the purposes of optimal controller design are investigated. A novel class of control laws is described in both continuous and discrete time; in the same way as the minimum variance regulator forms the basis of the self-tuning regulator of Åström and Wittenmark, these minimum variance controllers from the basis of a self-tuning controller. These minimum variance controllers have a number of advantages over the minimum-variance regulator, and are open to a number of interpretations including: a model following control law, and an extension of classical control laws to systems with delay. The optimality of this class of control laws is investigated, and analogies drawn with the previously considered k-step-ahead control laws; some examples are given to illustrate the method. An adaptive control law combining the above minimum variance controllers with a linear least-squares algorithm is proposed and shown to be self-tuning. These self-tuning controllers are only slightly more complex than the self-tuning regulator of Åström and Wittenmark, but have a number of advantages. Intuitive justification is given for the conjecture that some methods of Ljung, developed for the analysis of the self-tuning regulator, are applicable to the self-tuning controller. Simulated examples are given which compare and contrast the performance of the self-tuning controller with that of the self-tuning regulator. The first steps towards a quasi-continuous self-tuning controller are outlined.

Made available in DSpace on 2016-12-12T20:27:38Z (GMT). No. of bitstreams: 1 Aldo Zanella Junior.pdf: 3746857 bytes, checksum: 7ff548689a89fd8090402ad4891a23c1 (MD5) Previous issue date: 2015-07-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This work introduces the report of performed studies in order to evaluate the applicability of generalized predictive control (GPC) to several plants. The main goal is to analyze the GPC performance in processes with different features, analyzing the influence of its tuning parameters. The study is justified by the fact that GPC presents itself as a generalized solution for several classes of processes, which are becoming increasingly complex and demanding for traditional controllers to handle. For the purpose to prove this proposal of GPC, it was performed several tests with plants of different orders and response characteristics, real and simulated, varying controller tuning parameters and measuring some quality indices. It was evaluated the influence of tuning parameters and it was made a report of conclusions that was reached. Through obtained results, it is shown that GPC satisfies the proposal and presents favorable results. / Esta dissertação traz o relato do estudo realizado a fim de avaliar a aplicabilidade do controlador preditivo generalizado (GPC) em plantas diversas. O objetivo principal é analisar o desempenho do GPC em processos com diferentes características, analisando a influência dos seus parâmetros de sintonia. O estudo se justifica pelo fato de que o GPC apresenta-se como uma solução generalizada para diversos tipos de processos, os quais estão se tornando cada vez mais complexos e com maiores exigências para o controlador. A fim de comprovar essa proposta do GPC, realizou-se inúmeros ensaios com plantas com respostas e ordem diferentes, reais e simuladas, variando-se os parâmetros de sintonia do controlador e medindo-se alguns parâmetros de qualidade. Avaliou-se a influência dos parâmetros de sintonia e fez-se um relato das conclusões a que se chegou. Através dos resultados obtidos, mostra-se que o GPC corresponde ao que se propõe para as plantas testadas e apresenta resultados favoráveis.

The aim of the thesis is to improve the control quality of the adaptive systems (Self Tuning Controllers). The thesis mainly deals with problematical identification part of the adaptive system. This part demonstrates a weak point for existing adaptive systems. Paradoxically, the quality of the adaptive system depends mainly on the identification part because on the basis of the process model obtained by identification are worked out parameters of a control part, afterwards the control action plan is established. Knowledge of the modern control methods is used and a new identification algorithm for closed loop identification is proposed. This simple, fast and efficient algorithm overcomes all disadvantages of current classical identification methods based on least mean-square algorithms. The possibility of the choice of a short sample time, one tuning parameter ability to adjust the control process, the ability to identify processes in real use belong to its main goals. This algorithm was built in the adaptive system and then it was tested on a set of simulation and real models with surprisingly excellent results. The successful implementation of the algorithm into the programmable logic controller was also realized. One part of the thesis introduces a new universal graphics environment for testing and verifying control algorithms.