Optimal Path Controller Design of A Mobile Robot Based on T-S Fuzzy Model and Artificial Intelligence

• Main Authors: Yu-Hsuan Chen, 陳諭宣
• Other Authors: Gwo-Ruey Yu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/52986323360441772183

碩士 === 國立宜蘭大學 === 電機工程學系碩士班 === 98 === This paper proposed the path tracking design of a mobile robot based on Takagi-Sugeno (T-S) fuzzy modeling method and artificial intelligence algorithms. The T-S fuzzy model is utilized to represent the equation of motion of the mobile robot, and the concept of parallel distributed compensation (PDC) is applied to design the T-S fuzzy controller. The stability of the system is guaranteed by linear matrix inequalities (LMIs) from Lyapunov approach. However, the solutions of the LMIs can not ensure the system performance. To avoid the conservatives in design of the traditional T-S fuzzy membership functions, the hierarchical genetic algorithms (HGA) are employed to obtain the optimal solutions of the LMIs. In addition, the Taguchi method is used to search the best parameters of the HGA to reduce the numbers of experiments. Finally, the sliding mode control (SMC) preserves the advantages of quick response and low noise. Therefore, the T-S fuzzy control combine the SMC enable a mobile robot system to possess better robustness.