A Novel Stable Adaptive Fuzzy Sliding-Mode Control for Affine Nonlinear Systems with Large Uncertainties

• Main Authors: Chia-Ying Kuo, 郭佳穎
• Other Authors: Chih-Lyang Hwang
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/90634165089917167128

碩士 === 大同工學院 === 機械工程研究所 === 87 === In this thesis, a novel stable adaptive fuzzy sliding-mode control for affine highly nonlinear systems is developed. Based on the matching condition of uncertainties, a feedback linearizing control makes the system become a linear dynamic system with uncertainties. A reference model is designed to obtain an error model. Because the uncertainties are assumed to be large, a fuzzy-model is employed to model these uncertainties. A learning law with e-modification for the weight of fuzzy-model is designed to ensure the boundedness of estimated weight without the requirement of persistent excitation (PE) condition. Then, an equivalent control using the known part of system dynamics and the learning fuzzy-model is designed to achieve the desired control behavior. Furthermore, the uncertainties caused by the approximation of fuzzy-model and the error of estimated weight are tackled by the switching control. In summary, the proposed control includes a feedback linearizing control, an equivalent control and a switching control. Finally, the stability of the overall system is verified by the Lyapunov theory so that the ultimately bounded tracking is accomplished. Simulations and experiments of velocity control of four-bar-linkage system are presented to verify the usefulness of the proposed control