Adaptive Recurrent Fuzzy Cerebellar Model Articulation Controller Design for a Class of Nonlinear Systems

• Main Authors: Hsin-Min Wen, 温欣旻
• Other Authors: 彭椏富
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/40304870540705731484

碩士 === 清雲科技大學 === 電機工程所 === 101 === In this thesis, an adaptive intelligent indirect control system is developed for the uncertain nonlinear systems. This proposed control system is composed of two systems. One is a backstepping control system utilized as the main controller, in which an adaptive recurrent fuzzy cerebellar model articulation controller neural network is designed to identify the dynamics of the system models. Another one is a robust controller utilized to achieve system’s robust characteristics, which is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the adaptive intelligent indirect control system are derived based on the Lyapunov stability analysis, the Taylor linearization technique, backstepping control technique and control theory, so that the stability of the closed-loop system and tracking performance can be guaranteed. Finally, the proposed control system is applied to control a Duffing-Holmes chaotic system, a Genesio chaotic system, an inverted pendulum system and Chua’s chaotic system. From the simulation results, it is verified that the proposed control scheme can achieve favorable tracking performance for these nonlinear systems.