DocumentCode :
2415837
Title :
Intelligent Control for DC-DC Power Converter with Recurrent Fuzzy Neural Network Approach
Author :
Hsu, Chun-fei ; Lee, Tsu-Tian ; Wen, Yao-Wei ; Ding, Fu-Shan
Author_Institution :
Nat. Chiao-Tung Univ., Hsinchu
fYear :
0
fDate :
0-0 0
Firstpage :
457
Lastpage :
462
Abstract :
For many years, the control approaches for the dc-dc power converters are limited to PI controller structures. However, it gives the overshoot in output voltage as the rise time of response is reduced. To tackle this problem, an adaptive recurrent fuzzy neural network (ARENN) control system is developed in this paper. The on-line adaptive laws of the ARENN control scheme are derived based on the Lyapunov stability theorem, so that the stability of the system can be guaranteed. Experimental results show that the proposed ARFNN control scheme can achieve good regulation performances.
Keywords :
DC-DC power convertors; Lyapunov methods; PI control; adaptive control; control system synthesis; fuzzy control; fuzzy neural nets; neurocontrollers; power system control; recurrent neural nets; robust control; DC-DC power converter control; Lyapunov stability theorem; PI controller structure; adaptive recurrent fuzzy neural network control system development; intelligent control; online adaptive law; robust controller design; Adaptive control; Control systems; DC-DC power converters; Fuzzy control; Fuzzy neural networks; Intelligent control; Lyapunov method; Programmable control; Time factors; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2006 IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9488-7
Type :
conf
DOI :
10.1109/FUZZY.2006.1681751
Filename :
1681751
Link To Document :
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