Observer-based adaptive fuzzy decentralized control for stochastic large-scale nonlinear systems with unknown dead-zones

This paper studies the problem of adaptive fuzzy decentralized output feedback control for a class of uncertain stochastic large-scale nonlinear systems. The considered systems have unknown nonlinear functions, unknown dead-zones, unmodeled dynamics and unmeasurable state variables. Therefore, fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy state observer is established to estimate the unmeasurable states. Based on the backstepping design and the supply changing function technique, a robust adaptive fuzzy decentralized output feedback control approach is developed. The proposed control approach can ensure the closed-loop system to be input-state-practically stable (ISpS) in probability, and accommodate the unmodeled dynamics and unknown dead-zones as well. The effectiveness of the proposed control approach is illustrated by a simulation example.