Adaptive fuzzy sliding controller design with approximate error feedback

The research about sliding based approaches is a widely studied topic to the adaptive fuzzy control system designs. In this paper, a novel state error feedback sliding controller is proposed. An optimal feedback gain is required and in this study it is assumed to be unknown. Usually, a rudimentary feedback gain is used. Besides, in order to approximate the state error feedback sliding controller with the optimal feedback gain, an adaptive fuzzy system is employed. Thus, the proposed control scheme consists of an adaptive fuzzy system and a state error feedback sliding controller with a rudimentary feedback gain. In the system framework, the rudimentary state error feedback sliding controller can be viewed as the approximate error estimator of the adaptive fuzzy system. Therefore, such an estimated error can be fed back to the learning of the fuzzy system through a modified adaptive law. With such an approximate error feedback, it is clearly evident from our simulation that the learning speed of the proposed learning scheme is faster than that of the original scheme. Also, with the proposed controller, the system stability not only is guaranteed, but also becomes more stable.

[1]  An-Chyau Huang,et al.  Adaptive sliding control of active suspension systems with uncertain hydraulic actuator dynamics , 2003 .

[2]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[3]  Shun-Wen Tan,et al.  A New Approach to Chattering Reduction in the Sliding Mode Controls , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[4]  Jean-Pierre Barbot,et al.  Sliding Mode Control In Engineering , 2002 .

[5]  Tzu-Chun Kuo,et al.  Adaptive Sliding-Mode Control for NonlinearSystems With Uncertain Parameters , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  J.K. Liu,et al.  Global Sliding Mode Control with Adaptive Fuzzy Chattering Free Method for Nonlinear System , 2006, The Proceedings of the Multiconference on "Computational Engineering in Systems Applications".

[7]  L. Wang,et al.  Fuzzy systems are universal approximators , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[8]  Peter Kwong-Shun Tam,et al.  A fuzzy sliding controller for nonlinear systems , 2001, IEEE Trans. Ind. Electron..

[9]  An-Chyau Huang,et al.  Sliding control of non-linear systems containing time-varying uncertainties with unknown bounds , 2001 .

[10]  V. Utkin.  Variable structure systems with sliding modes , 1977 .

[11]  Li-Xin Wang,et al.  Stable adaptive fuzzy controllers with application to inverted pendulum tracking , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[12]  B. Kosko.  Fuzzy systems as universal approximators , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[13]  N. Pariz,et al.  Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control , 2006, 2006 IEEE Power Engineering Society General Meeting.

[14]  Bart Kosko,et al.  Fuzzy Systems as Universal Approximators , 1994, IEEE Trans. Computers.

[15]  F.H.F. Leung,et al.  A chattering elimination algorithm for sliding mode control of uncertain non-linear systems , 1998 .

[16]  G. D. Buckner.  Intelligent bounds on modeling uncertainty: applications to sliding mode control , 2002, IEEE Trans. Syst. Man Cybern. Part C.

[17]  Li-Xin Wang.  Stable adaptive fuzzy control of nonlinear systems , 1993, IEEE Trans. Fuzzy Syst..

[18]  Y. B. Shtessel,et al.  Chattering-free sliding mode control with unmodeled dynamics , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[19]  J. Farrell,et al.  Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series) , 2006 .

[20]  Chih-Min Lin,et al.  Adaptive fuzzy sliding-mode control for induction servomotor systems , 2004 .

[21]  Yoon Ho Choi,et al.  Chattering Free Sliding Mode Control , 2006, 2006 SICE-ICASE International Joint Conference.

[22]  W. Chang,et al.  Application of an auto-tuning neuron to sliding mode control , 2002 .

[23]  Xiaoping Zhu,et al.  A Novel Adaptive Fuzzy Control of the Inverted Pendulum System , 2007, 2007 IEEE International Conference on Control and Automation.

[24]  Rong-Jong Wai,et al.  Adaptive fuzzy sliding-mode control for electrical servo drive , 2004, Fuzzy Sets Syst..

[25]  Z. Zenn Bien,et al.  Robust adaptive fuzzy control in the presence of external disturbance and approximation error , 2004, Fuzzy Sets Syst..

[26]  Li-Xin Wang,et al.  A Course In Fuzzy Systems and Control , 1996 .

[27]  Vadim I. Utkin,et al.  Sliding mode control in electromechanical systems , 1999 .

[28]  Masayoshi Tomizuka,et al.  Chattering reduction and error convergence in the sliding-mode control of a class of nonlinear systems , 1996, IEEE Trans. Autom. Control..

[29]  E. Iglesias,et al.  Fuzzy surface-based sliding mode control. , 2007, ISA transactions.

[30]  Hebertt Sira-Ramírez,et al.  Control Design Techniques in Power Electronics Devices , 2006 .

[31]  Pushkin Kachroo,et al.  Existence of solutions to a class of nonlinear convergent chattering-free sliding mode control systems , 1999, IEEE Trans. Autom. Control..