Decentralized adaptive fuzzy tracking control for a class of uncertain large-scale systems with actuator nonlinearities

This paper studies the problem of decentralized adaptive tracking control for a class of nonlinear large-scale systems with unmeasurable states and actuator nonlinearities. For each subsystem, a novel decentralized disturbance rejection filter is designed to estimate both system states and external disturbances. The decentralized controller with adaptive laws is designed based on back-stepping techniques. It is proved that all the signals of the resulting closed-loop system are bounded, and the output tracking errors of subsystems converge to a desired neighborhood of origin. Simulation results illustrate the effectiveness of the method proposed in this paper.