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In this paper, an adaptive intelligent tracking control (AITC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This AITC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. The all adaptation laws of the AITC system are derived based on the Lyapunov stability analysis, so that the stability of the system can be guaranteed. Finally, the proposed AITC system is applied to control a Van der Pol oscillator and a Genesio chaotic system. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. [ABSTRACT FROM AUTHOR]

This paper investigates an intelligent adaptive robust control scheme for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. This control system is comprised of a recurrent cerebellar model articulation controller (RCMAC) and an auxiliary compensation controller. RCMAC is utilized to approximate a perfect controller, and the parameters of RCMAC are on-line tuned by the derived adaptive law from a Lyapunov function. Finally, two MIMO uncertain nonlinear systems, a mass-spring-damper system and a Chua's chaotic circuit, are performed to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]