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A NEW DESIGN APPROACH FOR FUZZY‐LEARNING FUZZY CONTROLLERS
Author(s) -
Tao C.W.,
Taur J.S.
Publication year - 2000
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2000.tb00160.x
Subject(s) - defuzzification , fuzzy set operations , fuzzy logic , neuro fuzzy , fuzzy classification , fuzzy number , fuzzy control system , control theory (sociology) , overshoot (microwave communication) , controller (irrigation) , adaptive neuro fuzzy inference system , artificial intelligence , computer science , membership function , fuzzy set , control engineering , mathematics , engineering , control (management) , telecommunications , agronomy , biology
In this paper, a new approach to designing fuzzy‐learning fuzzy controllers for a system plant without an exact mathematical model is presented. The cost function is defined as the square of the sliding function to alleviate the difficulty of overshoot when on‐line learning is conducted. The learning mechanism of a fuzzy controller is constructed so as to minimize the cost function with a set of linguistic rules. Moreover, to reduce the complexity of the fuzzy‐learning fuzzy controller, the fuzzy mechanism used for learning and the fuzzy mechanism contained in the fuzzy controller are designed so as to have the identical structures. Finally, simulations are included to show the effectiveness of the fuzzy‐learning fuzzy controllers.