DocumentCode :
1623490
Title :
Compact ant colony optimization algorithm based fuzzy neural network backstepping controller for MIMO nonlinear systems
Author :
Chen, Chao-Kuang ; Leu, Yih-Guang ; Wang, Wei-Yen ; Chen, Chun-Yao
Author_Institution :
Dept. of Ind. Educ., Nat. Taiwan Normal Univ., Taipei, Taiwan
fYear :
2010
Firstpage :
146
Lastpage :
149
Abstract :
In this paper, a compact ant colony algorithm used to tune parameters of fuzzy-neural networks is proposed for function approximation and adaptive control of nonlinear systems. In adaptive control procedure for nonlinear systems, weights of the fuzzy neural controller are online adjusted by the compact ant algorithm in order to generate appropriate control input. For the purpose of evaluating the stability of the closed-loop systems, an energy fitness function is used in the ant algorithm. Finally, a computer simulation example demonstrates the feasibility and effectiveness of the proposed method.
Keywords :
MIMO systems; adaptive control; closed loop systems; function approximation; fuzzy neural nets; neurocontrollers; nonlinear control systems; optimisation; MIMO nonlinear system; adaptive nonlinear control system; ant colony optimization algorithm; closed loop system; energy fitness function; function approximation; fuzzy neural controller; fuzzy neural network backstepping controller; parameter tuning; stability evaluation; Annealing; Chaos; Routing; adaptive control; ant colony algorithm; fuzzy neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Science and Engineering (ICSSE), 2010 International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-6472-2
Type :
conf
DOI :
10.1109/ICSSE.2010.5551754
Filename :
5551754
Link To Document :
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