Fuzzy-model-based robust stability of nonlinear networked control systems with input missing

This paper is concerned with fuzzy-model based robust stability of nonlinear networked control systems (NCSs) with time-varying transmission delays, transmission intervals and input missing based on a random-delay approach. The real-time distribution of input delays resulting from transmission delays and intervals is modeled as a dependent and nonidentically distributed process, and the occurrence of input missing is represented as a Bernoulli process. Then a randomly switched Takagi-Sugeno fuzzy system with multiple input-delay subsystems is proposed to model the nonlinear NCSs. Based on an improved Lyapunov-Krasovskii method, which takes into account the real-time distribution of input delays in estimating cross-product integral terms, new sufficient conditions are derived for the mean-square robust exponential stability of the overall systems. Numerical examples are presented to substantiate the effectiveness of our results.

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