DocumentCode :
2273221
Title :
Combined adaptive and fuzzy control using multiple models
Author :
Xu, Jian-Xin ; Liu, Chen ; Hang, Chang C.
Author_Institution :
Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
fYear :
1994
fDate :
26-29 Jun 1994
Firstpage :
22
Abstract :
This paper presents a control strategy to deal with processes in which both system parameters and orders are unknown and undergo abrupt structural variations. To handle such complicated control problems, a combined adaptive and fuzzy control scheme is developed. A number of generalized minimum variance (GMV) controllers are designed according to all the possible process structures. A higher level model selection mechanism decides which controller candidate is the best. A fuzzy modification algorithm is introduced to improve the system responses in transient period by detuning the control weights of GMV controllers. To cope with possible instability caused by non-minimum phase dynamics, a fuzzy PID backup is introduced as well. Some adaptation is added to the fuzzy PID backup to obtain better system performance
Keywords :
control system synthesis; dynamics; fuzzy control; model reference adaptive control systems; three-term control; adaptive control; fuzzy PID backup; fuzzy control; fuzzy modification algorithm; generalized minimum variance controllers; instability; model selection mechanism; multiple models; nonminimum phase dynamics; Adaptive control; Control system synthesis; Control systems; Fuzzy control; Fuzzy systems; Optimal control; Programmable control; System performance; Three-term control; Weight control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1896-X
Type :
conf
DOI :
10.1109/FUZZY.1994.343694
Filename :
343694
Link To Document :
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