Control solutions in mechatronics systems
Author(s) -
RaduEmil Precup,
Ștefan Preitl
Publication year - 2005
Publication title -
facta universitatis - series electronics and energetics
Language(s) - English
Resource type - Journals
eISSN - 2217-5997
pISSN - 0353-3670
DOI - 10.2298/fuee0503379p
Subject(s) - mechatronics , control theory (sociology) , fuzzy control system , fuzzy logic , parametric statistics , control system , control engineering , controller (irrigation) , equivalence (formal languages) , iterative learning control , adaptive neuro fuzzy inference system , computer science , mathematics , control (management) , engineering , artificial intelligence , agronomy , statistics , electrical engineering , discrete mathematics , biology
This paper presents control solutions dedicated to a class of controlled plants widely used in mechatronics systems, characterized by simplied mathematical models of second-order and third-order plus integral type. The conventional control solution is focused on the Extended Symmetrical Optimum method proposed by the authors in 1996. There are proposed six fuzzy control solutions employing PI-fuzzy controllers. These solutions are based on the approximate equivalence in certain con- ditions between fuzzy control systems and linear ones, on the application of the modal equivalence principle, and on the transfer of results from the continuous-time conven- tional solution to the fuzzy solutions via a discrete-time expression of the controller where Prof. Mili· R. Stoji· c's book (1) is used. There is performed the sensitivity analysis of the fuzzy control systems with respect to the parametric variations of the controlled plant, which enables the development of the fuzzy controllers. In addition, the paper presents aspects concerning Iterative Feedback Tuning and Iterative Learn- ing Control in the framework of fuzzy control systems. The theoretical results are validated by considering a real-world application.
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