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Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs. (English) Zbl 1282.93152
Summary: In this paper, adaptive neural control is proposed for a class of uncertain Multi-Input Multi-Output (MIMO) nonlinear state time-varying delay systems in a triangular control structure with unknown nonlinear dead-zones and gain signs. The design is based on the principle of sliding mode control and the use of Nussbaum-type functions in solving the problem of the completely unknown control directions. The unknown time-varying delays are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear functions outside the deadband as an added contribution. By utilizing the integral Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the approach.

MSC:
93C40 Adaptive control/observation systems
93C10 Nonlinear systems in control theory
93C41 Control/observation systems with incomplete information
93B51 Design techniques (robust design, computer-aided design, etc.)
93D30 Lyapunov and storage functions
92B20 Neural networks for/in biological studies, artificial life and related topics
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