Odporna regulacja predykcyjna obiektów nieliniowych

• Autorzy: Domek S.

Warianty tytułu

EN

Robust predictive control of nonlinear processes

• Języki publikacji: PL

Abstrakty

PL

Niniejsza praca, będąc wynikiem wieloletnich badań autora, zarówno teoretycznych, jak wdrożeniowych w przemyśle, stanowi próbę kompleksowego przedstawienia problematyki nieliniowej regulacji predykcyjnej oraz proponuje na tym tle łatwe do implementacji, dość uniwersalne i -jak się wydaje - skuteczne rozwiązanie suboptymalnej regulacji odpornej. Składa się z pięciu części tematycznych. W części pierwszej omówiono zasadę regulacji predykcyjnej, przedstawiono syntezę uogólnionego liniowego algorytmu predykcyjnego, a także wyjaśniono podstawowe właściwości układów regulacji predykcyjnej. Następnie sformułowano ogólne zadanie nieliniowej regulacji predykcyjnej oraz wskazano na istotne trudności jego rozwiązania, zwłaszcza w przypadku obiektów o niedokładnie znanych lub zmiennych w czasie właściwościach. W końcu przedstawiono najbardziej znane sposoby suboptymalnej regulacji NMPC, łącznie z metodami inteligencji obliczeniowej oraz scharakteryzowano najpopularniejsze i najchętniej stosowane w takiej regulacji postaci opisu obiektów nieliniowych, w tym modele rozmyte i neuronowe oraz bardzo popularne w praktyce tzw. modele blokowo-zorientowane. W części drugiej zaproponowano oryginalny sposób nieliniowej suboptymalnej regulacji predykcyjnej NL CRHPC z blokowo-zorientowanym modelem Hammersteina. Opisano dokładnie sposób syntezy algorytmu oraz jego rozwinięcie na przypadek wielowymiarowy, a także jego wersję uproszczoną, ułatwiającą implementację w systemach mikroprocesorowych o szczególnie małej mocy obliczeniowej. Następnie zaproponowano syntezę wielowymiarowego algorytmu z modelem Hammersteina w dziedzinie zmiennych stanu NL MPCS. Dla obu algorytmów podano sposób uwzględnienia ograniczeń sygnału sterującego. W części trzeciej zaproponowano włączenie opracowanych i opisanych wcześniej suboptymalnych, nieliniowych regulatorów predykcyjnych z modelem Hammersteina w strukturę regulacji ze śledzeniem modelu MFC, charakteryzującą się zwiększoną odpornością w stosunku do klasycznych układów jednopętlowych. Opisano zasadę doboru regulatora pomocniczego układu NMPC-MFC dla obiektów SISO oraz sposób suboptymalnego ograniczenia sygnału sterującego. W części czwartej przedstawiono wersję odpornego, nieliniowego układu regulacji NMPC-MFC dla obiektów o wielu wejściach i wielu wyjściach. Dokonano syntezy regulatorów składowych proponowanej struktury układu regulacji przy założeniu, że obiekt podlegać może nieznanym, ale ograniczonym perturbacjom oraz że działać na niego mogą zależne w znany sposób od wektora stanu, ale niekoniecznie ograniczone zakłócenia. W końcowej części pracy całość rozważań teoretycznych zilustrowano wynikami przykładowych badań symulacyjnych proponowanych algorytmów. Pokazano również wyniki regulacji rzeczywistego obiektu elektotermicznego rozproszonym systemem PAC, w którym zaimplementowano opracowany algorytm odpornego sterowania predykcyjnego.

EN

In the monograph an approach to synthesis of a predictive controller for nonlinear processes that are sufficiently adequately described by a Hammerstein model is presented. To extend the range of applicability of the control algorithm to nonlinear processes the properties of which depart from those defined by the adopted model, it has been proposed to incorporate the algorithm into the Model Following Control (MFC) structure characterized by high robustness. In the first part of the monograph the principle of predictive control is discussed, and synthesis of a generalized linear predictive control algorithm is presented. Also, basic system properties and ways to provide stability for predictive control systems are established. Further, the nonlinear predictive control and the ways of its implementation are described. The second part deals with nonlinear predictive control that employs a Hammerstein model. The structure and properties of the model are discussed. Also, synthesis of the control algorithm is described, and its extension to multivariable control is given. A modification of the proposed algorithm that enables its implementation in microcomputer systems of low computing power is presented. Next, synthesis of the multivariable algorithm with the Hammerstein model in state space is given. The synthesis method is based on representing nonlinear time-invariant processes by their linear time-variant models. The third part is devoted to increasing the robustness exhibited by the control system with the proposed predictive algorithms to an inevitable mismatch between the process model adopted for controller synthesis and the actual process. The increase in robustness has been achieved by incorporating the developed predictive algorithms into the MFC structure. After presenting general characteristics featured by MFC, a description of the proposed predictive NMPC-MFC controller with the Hammerstein model for SISO or multivariable diagonally dominated processes is given. In the fourth part of the monograph a robust predictive NMPC-MFC controller for MIMO processes is presented. The controllers making up the MFC structure have been synthesized under assumption that the process to be controlled may be subjected to unknown yet bounded perturbations, or may be affected by disturbances not necessarily bounded yet dependent on the state vector in a known way. The applicability of the theoretical study is illustrated by results of simulation tests. Additionally, results of tests are given where a real electrothermal plant is governed by a distributed Programmable Automation Controller (PAC) system in which the proposed predictive control algorithm has been implemented. It has been shown that the proposed solutions are easy to implement, and provide relatively high robustness and control performance. Another virtue is that the proposed solutions retain advantages inherent in linear predictive algorithms, such as simple physical interpretation and the ease of identification of the adopted process model. Also, the nonlinear algorithm parameters to be tuned may be chosen by means of methods recommended for corresponding linear algorithms. The operation principle of the proposed MFC structure is relatively intelligible, and the structure itself may be implemented without any difficulties and without any powerful computing means. Moreover, due to its universality the proposed NMPC-MFC structure may be utilized in robust controllers based on predictive algorithms other than those proposed in the monograph in order to control nonlinear processes or those with time-variant parameters.

Słowa kluczowe

PL

regulacja predykcyjna; regulacja nieliniowa; regulacja odporna; model Hammersteina; algorytm predykcyjny; układ odporny; układ MFC

• Wydawca: Wydawnictwo Uczelniane Politechniki Szczecińskiej
• Czasopismo: Prace Naukowe Politechniki Szczecińskiej. Instytut Automatyki Przemysłowej
• Rocznik: 2006
• Tom: Nr 593 (20)
• Strony: 1--205
• Opis fizyczny: Bibliogr. 310 poz., rys., tab.

Twórcy

autor

Domek S.

Bibliografia

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