Adaptive fuzzy decentralized control for stochastic large-scale nonlinear systems with unknown dead-zone and unmodeled dynamics

In this paper, an adaptive fuzzy decentralized control approach is proposed for a class of uncertain large-scale stochastic nonlinear systems with unknown functions, unknown dead-zone and unmodeled dynamics. In the controller design, fuzzy logic systems are used to approximate the unknown nonlinear functions, and by combining the backstepping recursive design with the dynamical signal technique, a robust adaptive fuzzy decentralized control approach is developed. It is proved that the proposed control approach can guarantee that the closed-loop system is input-state-practically stability (ISpS) in probability, and the output of the system converges to a small neighborhood of the origin in the presence of unknown dead-zone and unmodeled dynamics. A simulation example is provided to show the effectiveness of the proposed control approach.

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