Fuzzy-neural sliding-mode control for DC-DC converters using asymmetric gaussian membership functions

Kuo Hsiang Cheng, Chun Fei Hsu, Chih Min Lin, Tsu Tian Lee, Chunshien Li

Research output: Contribution to journalArticlepeer-review

140 Scopus citations


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.

Original languageEnglish
Pages (from-to)1528-1536
Number of pages9
JournalIEEE Transactions on Industrial Electronics
Issue number3
StatePublished - Jun 2007


  • Adaptive control
  • Asymmetric gaussian membership function
  • Converter
  • Fuzzy neural network
  • Sliding-mode control


Dive into the research topics of 'Fuzzy-neural sliding-mode control for DC-DC converters using asymmetric gaussian membership functions'. Together they form a unique fingerprint.

Cite this