Decentralized adaptive fuzzy control for nonlinear large-scale systems with random packet dropouts, sensor delays and nonlinearities

This paper investigates the adaptive fuzzy decentralized control problem for a class of uncertain nonlinear large-scale systems. Different from the conventional backstepping-based adaptive output feedback control technique, the output measurements are imperfect and considered to suffer random packet dropouts (RPDs), random sensor delays (RSDs) and random sensor nonlinearities (RSNs), which result typically from a network environment such as sensor networks. A novel sensor model is established for describing the random phenomena within a unified representation by introducing a multi-Markovian variable. Based on this sensor model, two main difficulties arise: first is that the system output cannot be used directly for controller design due to the randomly occurring phenomena; second is how to deal with the complex nonlinear stochastic terms with unknown interconnections, unknown time-varying delays and unknown sensor nonlinearities entangled together. With the help of new coordinate transformations and mean value theorem, by using appropriate Lyapunov-Krasovskii functionals, a new adaptive decentralized memoryless output feedback controller is designed. It is proved that the constructed controller ensures the boundedness in probability of all the closed-loop signals in presence of RPDs, RSDs and RSNs. The simulation results are presented to show the effectiveness of the proposed scheme.