An output-feedback fuzzy approach to guaranteed cost control of vehicle lateral motion |
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| Authors: | Chen-Sheng Ting |
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| Affiliation: | 1. Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;2. Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China;1. Laboratory of Sciences and Techniques of Automatic Control & Computer Engineering (Lab-STA), National School of Engineering of Sfax, University of Sfax, Postal Box 1173, 3038 Sfax, Tunisia;2. Modeling, Information, and Systems Laboratory, University of Picardie Jules Verne, Amiens 80000, France;1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, People?s Republic of China;2. Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai 200240, People?s Republic of China;3. Institute of Automation, Beijing University of Chemical Technology, Beisanhuan East Road 15, Chaoyang District, Beijing 100029, People?s Republic of China;1. Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S4L8, Canada;2. School of Mechanical Engineering, Southeast University, Nanjing 211189, PR China;3. School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, PR China;4. University of Picardie Jules Verne, MIS (E.A. 4290). 80039, Amiens, France |
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| Abstract: | This paper introduces a fuzzy guaranteed cost control approach for automated steering of a highway vehicle. The Takagi–Sugeno (T–S) fuzzy model is utilized to depict the dynamics of nonlinear time-varying lateral system. Based on the fuzzy model, an observer-based fuzzy controller is developed so that without knowing road’s curvature the vehicle can track center of the present lane on a curved highway section. Integrating H∞ control and optimal control strategies, the fuzzy controller and observer are formulated by solving a minimization problem, which is to minimize a given quadratic performance function. Sufficient conditions to ensure minimum upper bound of the performance function are derived in terms of linear matrix inequalities (LMIs). Therefore, the designing work can be efficiently completed by applying the convex optimization techniques. Verified by computer simulation, the proposed method can perform well in driving safety and ride comfort. |
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