Adaptive Fuzzy Robust Control of a Class of Nonlinear Systems via Small Gain Theorem
This paper presents a novel adaptive fuzzy robust control (AFRC) algorithm for a class of nonlinear systems with partly linearly parameterized system models, unknown system nonlinearities and external unknown disturbances. For linearly parameterized system models, discontinuous-projection-based adaptive control law is used to estimate system parameters. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown system nonlinearities. Robust control law ensures the robustness of closed-loop control system. This proposed AFRC effectively combines techniques of adaptive control and fuzzy control and it improves control performance by retaining the advantages of both. A systematic design procedure of AFRC is developed by combining the backstepping technique and smallgain approach. The closed-loop stability is studied using small gain theorem and the control system is proved to be semi-globally uniformly ultimately bounded.
adaptive control fuzzy control robust control nonlinear system small gain theorem
Xingjian Wang Shaoping Wang Kang Wang Wei Hong
School of Automation Science and Electric Engineering, Beihang University Beijing 100191, China Scie School of Automation Science and Electric Engineering, Beihang University Beijing 100191, China School of Automation Science and Electric Engineering, Beihang University Beijing 100191, China Scie
国际会议
IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)
北京
英文
559-564
2012-07-25（万方平台首次上网日期，不代表论文的发表时间）