Predictive Control for Takagi–Sugeno Fuzzy Large-Scale Networked Control Systems

In this paper, the issue of exponential stabilization and sampled-data controller design for Takagi–Sugeno fuzzy large-scale networked control systems is studied by using the reduction-based ordinary differential equation prediction method. For the problem that matrices cannot be multiplied directly during the process of designing the sampled-data controller in this paper, a matrix dimensional transformation method is proposed. Firstly, a type of two-sided mode-dependent loop-based Lyapunov–Krasovskii functional is constructed, which compensates for the large delay and makes fuller use of the information in sampled-data interval. Secondly, the proposed method is used to give the design scheme of an aperiodic sampled-data controller, and furthermore, an iterative algorithm to verify the effectiveness of the requested control gains is provided. Finally, two coupled vehicle pendulum systems and two-area interconnected power systems are applied to demonstrate the efficiency of the presented approach.