Abstract
SummaryThis paper investigates the adaptive fuzzy prescribed performance output‐feedback decentralized control problem for a class of stochastic interconnected nonlinear large‐scale systems. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a state observer is designed to estimate the unmeasured states. By combining the backstepping recursive design principle with prescribed performance theory, an adaptive fuzzy decentralized control method is presented. In order to overcome the problem of “explosion of complexity” in the adaptive backstepping control design, the first‐order filter signals are introduced into adaptive fuzzy decentralized control design algorithm and form a new simplized. The stability is proven based on the Lyapunov stability theory, which demonstrated that all the signals of the closed‐loop system are semiglobally uniformly ultimately bounded in probability and the tracking errors remain a small neighborhood of the origin within the prescribed performance bounds. Finally, a simulation example is provided to illustrate the effectiveness of the proposed approach.
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