Adaptive intelligent tracking control system for uncertain nonlinear systems using ORCMAC

In this paper, an adaptive intelligent tracking control (AITC) system employs an output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system. In the AITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis and the H^infin control technique, so that the stability of the closed-loop system can be guaranteed. Finally, the proposed control system is applied to control an inverted pendulum system and a Genesio chaotic system. Simulation results demonstrate that the proposed control scheme can achieve favorable tracking performances for the uncertain nonlinear systems with unknown dynamic functions and under the occurrence of external disturbance.