DocumentCode :
637140
Title :
Output tracking of fractional-order nonlinear systems via TS-FCMAC
Author :
Tung-Sheng Chiang ; Chian-Song Chiu
Author_Institution :
Dept. of Electr. Eng., Chien Hsin Univ. of Sci. & Technol., Chungli, Taiwan
fYear :
2013
fDate :
16-19 April 2013
Firstpage :
51
Lastpage :
56
Abstract :
The purpose of article is to develop a general Takagi-Sugeno fuzzy cerebellar model articulation controller (TS-FCMAC) and to apply to the tracking controller of fractional-order nonlinear systems. In this paper, a novel TS-CMAC controller is developed in two cases: off-line and on-line learning. First, the off-line learning convergence of TS-FCMAC is analyzed and is confined to a least square error, when the learning rate approaches to zero as the iteration goes to infinity. The benefit is having high potential to functional learning by simpler network structure. Second, the on-line learning TS-FCMAC is designed to assure tracking control. Also, we apply the TS-CMAC to realize the ideal control law for fractional-order nonlinear systems and to achieve asymptotic stability. Finally, simulation results demonstrate the validity of the purposed control scheme.
Keywords :
asymptotic stability; cerebellar model arithmetic computers; fuzzy control; least mean squares methods; neurocontrollers; nonlinear control systems; TS-FCMAC; Takagi-Sugeno fuzzy; asymptotic stability; cerebellar model articulation controller; fractional-order nonlinear system; functional learning; least square error; off-line learning; online learning; output tracking controller; Approximation methods; Control systems; Convergence; Fuzzy control; Neural networks; Nonlinear systems; Time factors; FCMAC; fractional-order nonlinear systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Control and Automation (CICA), 2013 IEEE Symposium on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/CICA.2013.6611663
Filename :
6611663
Link To Document :
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