ROBUST SELF-CONSTRUCTING PARAMETRIC CEREBELLAR MODEL ARTICULATION CONTROLLER DESIGN FOR A CLASS OF NONLINEAR SYSTEMS

• Main Authors: Jian-Lang Lai, 賴建郎
• Other Authors: Hung-Ching Lu
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/89374265690061604880

碩士 === 大同大學 === 電機工程學系(所) === 96 === The design of the robust self-constructing parametric cerebellar model articulation controller (RSCP-CMAC) for a class of nonlinear systems is proposed in this thesis. The proposed controller is composed of a self-constructing parametric CMAC (SCP-CMAC) and a robust controller. The SCP-CMAC, which has the ability in generating and eliminating the association indexes of CMAC, is utilized to approximate the ideal controller so that the corresponding memory size of the proposed controller can be reduced effectively. The robust controller is designed to achieve a specified robust tracking performance of the system. Besides, the concept of sliding-mode control (SMC) is adopted in the control scheme, and therefore, the proposed controller has more robustness against the uncertainties and the approximated error. Furthermore, based on the Lyapunov function, the adaptive laws of the RSCP-CMAC are derived so that the stability of the system can be guaranteed. Finally, the proposed controller is applied to the second-order chaotic system, Chua’s chaotic system, and one-link rigid robotic manipulator. Simulation results show the good tracking performance of the proposed controller and verify its effectiveness.