Study of the Intelligent Robust Controllers and their Applications

• Main Authors: Chien-An Chen, 陳建安
• Other Authors: Huann-Keng Chiang
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/35061655381240669510

博士 === 雲林科技大學 === 工程科技研究所博士班 === 97 === This dissertation put focus on the adaptive estimator, adaptive fuzzy estimator and Gaussian radial basis function neural network (GRBFNN) estimator. They are combined with sliding mode control and backstepping control which design robust stabilization, disturbance rejection of the synchronous reluctance motor (SynRM) drive system, and the magnetic ball suspension system (MBSS). In general, it is assumed that the upper bounds of parameter variations and external disturbances are known and the sign function is used when people use the conventional sliding mode control and conventional backstepping control design. As a result, high frequency chattering and high gain phenomenon occurred. So, in this dissertation, it is proposed that three estimators of sliding mode control and backstepping control for the SynRM and MBSS would reduce the magnitude of the chattering or could avoid the chattering. In order to validate the proposal, I utilize Lyapunov function to guarantee the convergence and track the command of the SynRM and MBSS asymptotically. These estimators of parameter variations and external disturbances estimate the unknown lumped uncertainty in real time. Besides, they are different from the conventional adaptive sliding mode control and conventional adaptive backstepping control when estimating the unknown uncertainty upper boundary. In my dissertation, these proposed methods are validated by experiments.