T-S Fuzzy Controller Design via Real-Valued Genetic Algorithms and LMI with Applications in a Model Car

• Main Authors: Hsyueh-Pin Wang, 王學彬
• Other Authors: Hung-Yuan Chung
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/54407178045251375506

碩士 === 國立中央大學 === 電機工程研究所 === 91 === In this paper, we propose a new algorithm to design the Takagi- Sugeno fuzzy controller via Real-Valued Genetic Algorithm (GA) and LMI (Linear Matrix Inequalities) technique. Because this algorithm combines the advantages of GA and LMI, one can design the feedback gains of the controller according to characteristics and required Performances of each system. Hence, this method can improve the drawbacks of general LMI-based design ones. This thesis first discusses the design of the controller of the trajectory stabilization of a model car. Then we dilate on the process of design controller by two different ways and compare them by means of simulations. In order to show the feasibility and the applicability of this method, we explain how to devise and create a model car and verify it with the T-S fuzzy controller based on the GA and LMI.