| Summary: | 碩士 === 中華技術學院 === 電子工程研究所碩士班 === 95 === A robust fuzzy neural controller for a class of uncertain nonlinear dynamical systems is proposed and analyzed. The controller combines fuzzy system, CMAC and sliding mode, achieve the stable of closed loop system. The adaptive fuzzy CMAC incorporates the CMAC into the THEN-Part of fuzzy system, so that a simplified fuzzy CMAC can be achieved. The weights of CMAC as well as the parameters of fuzzy system can be tuned in real time operation. The system stability and parameters convergence of fuzzy CMAC can be guaranteed with Lyapunov stability analysis. Finally, two nonlinear systems, a planetary train type inverted pendulum system and an electric drive system are respectively utilized to prove the satisfactory performances of the proposed control scheme.
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