Adaptive output-feedback inverse control for a class of time delay nonlinear hysteretic systems via fuzzy approximator

In this paper, an fuzzy approximator based output feedback adaptive dynamic surface inverse control (DSIC) scheme is proposed for a class of time-delay systems preceded by unknown asymmetric hysteresis. The main advantages are as follows: 1) by combining the Finite Covering Lemma with fuzzy logic systems (FLSs), a novel time-delay function approx-imator is proposed with the benefits of the assumptions of the conservative upper bound functions on the time-delay functions are removed and the Krasovskii functionals are not required when deal with time delays. Also, the time delay functions extends to a more general one with states variables and time-delay variables being coupled; 2) by using the proposed initial technique, the Lnorm of the tracking error is obtained; 3) by constructing the inverse of the asymmetric hysteresis and approximating the unknown time-delay functions, both time delays and asymmetric hysteresis phenomena in the actuators are mitigated simultaneously when only the output of the system is available. It is proved that all the signals in the closed-loop systems are semi-globally ultimately uniformly bounded (SUUG). Simulation results show the validity of the proposed scheme.

[1]  Shuzhi Sam Ge,et al.  Adaptive Neural Control for a Class of Nonlinear Systems With Uncertain Hysteresis Inputs and Time-Varying State Delays , 2009, IEEE Transactions on Neural Networks.

[2]  Xinkai Chen,et al.  Adaptive Control for Uncertain Continuous-Time Systems Using Implicit Inversion of Prandtl-Ishlinskii Hysteresis Representation , 2010, IEEE Transactions on Automatic Control.

[3]  Bing Chen,et al.  Adaptive Neural Control for a Class of Perturbed Strict-Feedback Nonlinear Time-Delay Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[4]  Y. Stepanenko,et al.  Adaptive control of a class of nonlinear systems with fuzzy logic , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[5]  Chun-Yi Su,et al.  Adaptive control of a class of nonlinear systems with fuzzy logic , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[6]  Xinkai Chen,et al.  Modeling and inverse adaptive control of asymmetric hysteresis systems with applications to magnetostrictive actuator , 2014 .

[7]  Chun-Yi Su,et al.  Modeling and robust adaptive control of metal cutting mechanical systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[8]  Yan Lin,et al.  Adaptive Neural Network Dynamic Surface Control for a Class of Time-Delay Nonlinear Systems With Hysteresis Inputs and Dynamic Uncertainties , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[9]  Tieshan Li,et al.  Output-Feedback Adaptive Neural Control for Stochastic Nonlinear Time-Varying Delay Systems With Unknown Control Directions , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Yan Lin,et al.  Adaptive control for a class of nonlinear time-delay systems preceded by unknown hysteresis , 2013, Int. J. Syst. Sci..