Decentralized Guaranteed Cost Control for Discrete-time Uncertain Large-scale Systems Using Fuzzy Control

This paper investigates an application of fuzzy control to the guaranteed cost control problem of decentralized robust control for a class of discrete-time uncertain large-scale systems. Based on linear matrix inequality (LMI) design approach, a class of decentralized local fixed state feedback controllers with additive gain perturbations is established. The novel contribution of this paper is that in order to reduce the large cost caused by the LMI conditions, the fuzzy controllers are substituted for the additive gain perturbations. Although the fuzzy controllers are included in the uncertain large-scale systems, the closed-loop system is asymptotically stable. As another important feature, the control input matrices allow uncertainty and the conservative assumption is not needed compared with the existing result that is based on the neural networks. In order to demonstrate the efficiency of our proposed controller, the simple numerical example is given.