Backstepping adaptive fuzzy control of uncertain nonlinear systems against actuator faults

被引：86

作者：

Li P. ^{[1
]}

Yang G. ^{[1
]}

机构：

[1] Key Laboratory of Integrated Automation for the Process Industry, Ministry of Education, and College of Information Science and Engineering, Northeastern University

来源：

Journal of Control Theory and Applications | 2009年 / 7卷 / 3期

基金：

中国国家自然科学基金;

关键词：

Actuator fault; Adaptive control; Backstepping; Fuzzy system; Uncertain nonlinear system;

D O I：

10.1007/s11768-009-8074-6

中图分类号：

学科分类号：

摘要：

A class of unknown nonlinear systems subject to uncertain actuator faults and external disturbances will be studied in this paper with the help of fuzzy approximation theory. Using backstepping technique, a novel adaptive fuzzy control approach is proposed to accommodate the uncertain actuator faults during operation and deal with the external disturbances though the systems cannot be linearized by feedback. The considered faults are modeled as both loss of effectiveness and lock-in-place (stuck at some unknown place). It is proved that the proposed control scheme can guarantee all signals of the closed-loop system to be semi-globally uniformly ultimately bounded and the tracking error between the system output and the reference signal converge to a small neighborhood of zero, though the nonlinear functions of the controlled system as well as the actuator faults and the external disturbances are all unknown. Simulation results demonstrate the effectiveness of the control approach. © South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag GmbH 2009.

引用

页码：248 / 256

页数：8

共 27 条

[1]

Wang L., Mendel J.M., Fuzzy basis functions, universal approximation, and orthogonal least-squares learning[J], IEEE Transactions on Neural Networks, 3, 5, pp. 807-814, (1992)

[2]

Wang L., Stable adaptive fuzzy control of nonlinear systems[J], IEEE Transactions on Fuzzy Systems, 1, 2, pp. 146-155, (1993)

[3]

Chen B.S., Lee C.H., Chang Y.C., H<sub>∞</sub> tracking design of uncertain nonlinear SISO systems: Adaptive fuzzy approach[J], IEEE IEEE Transactions on Fuzzy Systems, 4, 1, pp. 32-43, (1996)

[4]

Koo T.J., Stable model reference adaptive fuzzy control of a class of nonlinear systems[J], IEEE Transactions on Fuzzy Systems, 9, 4, pp. 624-636, (2001)

[5]

Han H., Su C., Stepanenko Y., Adaptive control of a class of nonlinear systems with nonlinearly parameterized fuzzy approximators[J], IEEE Transactions on Fuzzy Systems, 9, 2, pp. 315-323, (2001)

[6]

Hojati M., Gazor S., Hybrid adaptive fuzzy identification and control of nonlinear systems[J], IEEE Transactions on Fuzzy Systems, 10, 2, pp. 198-210, (2002)

[7]

Li H., Tong S., A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems[J], IEEE Transactions on Fuzzy Systems, 11, 1, pp. 24-34, (2003)

[8]

Yang Y., Feng G., Ren J., A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems[J], IEEE Transactions on Systems, Man and Cybernetics-Part A, 34, 3, pp. 406-420, (2004)

[9]

Yang Y., Zhou C., Adaptive fuzzy H<sub>∞</sub> stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach[J], IEEE Transactions on Fuzzy Systems, 13, 1, pp. 104-114, (2005)

[10]

Tong S., Li Y., Direct adaptive fuzzy backstepping control for nonlinear systems[C], First International Conference on Innovative Computing, Information and Control, pp. 623-627, (2006)

← 1 2 3 →