Improvement on fuzzy-model-based stabilization of nonlinear networked control systems

This paper is concerned with an improvement on fuzzy-model-based stabilization of nonlinear networked control systems (NCSs) with time-varying transmission delays and transmission intervals. The real-time distribution of input delays is taken into account and modeled as a dependent and nonidentically distributed process. A randomly switched Takagi-Sugeno (T-S) fuzzy system with multiple input-delay subsystems is proposed to model the nonlinear NCSs. Based on an improved Lyapunov-Krasovskii method, which appropriately takes into account the real-time distribution of input delays in estimating cross-product integral terms and the characteristics of T-S fuzzy model, new sufficient conditions are derived for the deterministic asymptotical stability of the overall systems. The resulting controller design method is equivalent to a nonlinear convex optimization problem with LMI constraints. Numerical examples are presented to substantiate the effectiveness and advantage of our results.