Fuzzy-model-based fault detection for nonlinear networked control systems with periodic access constraints and Bernoulli packet dropouts

Abstract

In this paper, the problem of fault detection for nonlinear networked control systems subject to both communication constraints and packet dropouts is investigated. Despite the huge bulk of studies in the area of linear networked control systems, nonlinear networked control systems have been less involved. In the proposed method, Takagi–Sugeno fuzzy model is employed to represent nonlinear networked control systems. To model the communication network, access constraints and packet dropouts are respectively considered as periodic sequences and Bernoulli processes. Based on the optimal periodic residual generator theory, a fuzzy-model-based observer is proposed to deal with the problem of fault detection for nonlinear networked control systems. Both residual evaluation and correspondence threshold are also investigated to generate confident fault alarms. Finally, the effectiveness of the proposed fault detection scheme for nonlinear networked control systems is illustrated and some simulation results are carried out to validate the proposed approach.