Fault detection for stochastic parameter-varying Markovian jump systems with application to networked control systems

This paper investigates the fault detection (FD) problem for networked control systems (NCS). The random delays from the sensor to the controller (S-C) and from the controller to the actuator (C-A) are modeled as a Markov chain. Whilst considering the data dropout phenomenon happens unavoidably and the measurement drops intermittently, C-A data dropout and S-C data dropout are coped with by introducing two independent Bernoulli processes. Based on the above two points, a stochastic parameter-varying Markovian jump system (SPVMJS) is constructed. By combining discrete Parseval theorem and strict S-procedure, a novel finite frequency approach is proposed to design an H−/H∞ fault detection filter for the SPVMJSs. Finally, a simulation example on the networked control system is presented to illustrate the effectiveness of the proposed method.