Sampled observer-based adaptive decentralized control for strict-feedback interconnected nonlinear systems

Abstract

This paper investigates the decentralized tracking control problem for a class of strict-feedback interconnected nonlinear systems with unknown parameters, where the system states are unmeasurable and the interconnections are unknown. Different from the existing results, where the output is available all the time, we consider the case that the output is only available at the sampled instants, which means the failure of existing methods. By introducing a kind of sampled observer for each subsystem, the system states and unknown parameters are jointly estimated. Based on which, a totally decentralized output feedback control scheme is developed to achieve the desired tracking performance by applying backstepping technique, where a compensation mechanism is utilized to address the unknown interconnections from other subsystems. Subsequently, by using Lyapunov stability theory, it is proved that all the signals in the closed-loop system are bounded and the tracking errors converge to an adjustable neighbourhood of the origin. Finally, an example is used to illustrate the effectiveness of the proposed method.