TY - JOUR
T1 - Fuzzy-neural sliding-mode control for DC-DC converters using asymmetric gaussian membership functions
AU - Cheng, Kuo Hsiang
AU - Hsu, Chun Fei
AU - Lin, Chih Min
AU - Lee, Tsu Tian
AU - Li, Chunshien
N1 - Funding Information:
Manuscript received September 10, 2005; revised November 14, 2005. This work was supported in part by the National Science Council of the Republic of China under Grant NSC 93-2213-E-155-038. K.-H. Cheng is with the Department of Electrical Engineering, Chang Gung University, Tao-Yuan 333, Taiwan, R.O.C. (e-mail: d9021010@stmail. cgu.edu.tw). C.-F. Hsu is with the Department of Electrical Engineering, Chung Hua University, Hsinchu 300, Taiwan, R.O.C. (e-mail: [email protected]). C.-M. Lin is with the Department of Electrical Engineering, Yuan Ze University, Tao-Yuan 320, Taiwan, R.O.C. (e-mail: [email protected]). T.-T. Lee is with the Department of Electrical Engineering, National Taipei University of Technology, Taipei 106, Taiwan, R.O.C. (e-mail: ttlee@ ntut.edu.tw). C. Li is with the Department of Computer Science and Information Engineering, National University of Tainan, Tainan 700, Taiwan, R.O.C. (e-mail: [email protected]). Digital Object Identifier 10.1109/TIE.2007.894717
PY - 2007/6
Y1 - 2007/6
N2 - A fuzzy-neural sliding-mode (FNSM) control system is developed to control power electronic converters. The FNSM control system comprises a neural controller and a compensation controller. In the neural controller, an asymmetric fuzzy neural network is utilized to mimic an ideal controller. The compensation controller is designed to compensate for the approximation error between the neural controller and the ideal controller. An online training methodology is developed in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Finally, to investigate the effectiveness of the FNSM control scheme, it is applied to control a pulsewidth-modulation-based forward dc-dc converter. Experimental results show that the proposed FNSM control system is found to achieve favorable regulation performances even under input-voltage and load-resistance variations.
AB - A fuzzy-neural sliding-mode (FNSM) control system is developed to control power electronic converters. The FNSM control system comprises a neural controller and a compensation controller. In the neural controller, an asymmetric fuzzy neural network is utilized to mimic an ideal controller. The compensation controller is designed to compensate for the approximation error between the neural controller and the ideal controller. An online training methodology is developed in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Finally, to investigate the effectiveness of the FNSM control scheme, it is applied to control a pulsewidth-modulation-based forward dc-dc converter. Experimental results show that the proposed FNSM control system is found to achieve favorable regulation performances even under input-voltage and load-resistance variations.
KW - Adaptive control
KW - Asymmetric gaussian membership function
KW - Converter
KW - Fuzzy neural network
KW - Sliding-mode control
UR - http://www.scopus.com/inward/record.url?scp=48949097083&partnerID=8YFLogxK
U2 - 10.1109/TIE.2007.894717
DO - 10.1109/TIE.2007.894717
M3 - 期刊論文
AN - SCOPUS:48949097083
SN - 0278-0046
VL - 54
SP - 1528
EP - 1536
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 3
ER -