Fault Estimation for Semi-Markov Jump Cyber-Physical Control Systems With External Disturbances

Abstract

The main thrust of this study is to scrutinize the issues of fault estimation and asynchronous sampled-data fault-tolerant control for semi-Markov jump cyber-physical systems with external disturbances, faults and deception attacks. To do so, initially, an intermediate variable is framed and then using that variable as a foundation, a mode-dependent intermediate estimator is constructed, which estimates the fault signals and system's state simultaneously. Due to the unavailability of mode information in the Markov chain for the observer/controller, a hidden Markov model is employed to represent the asynchronous scenario between the mode of the original system and that of the designed observer/controller. Subsequently, benefited by the estimated terms and sampled-data approach, an asynchronous sampled fault-tolerant control protocol is offered up that facilitates compensating for the faults occurring in the system. In the meantime, the extended passive performance is used to lessen the negative impact of external disturbances exerting on the system. Besides this, the deception attacks occurring in the system are presumed to have a stochastic nature that adheres to the Bernoulli distribution. Moreover, by constructing mode-dependent Lyapunov–Krasovskii functional and blending it with integral inequalities, the sufficient condition confirming the intended outcomes is procured in the framework of linear matrix inequalities. Thereafter, on the platform of deduced adequate criteria, an explicit formulation for the requisite gain values can be obtained. Ultimately, simulation results are offered to verify the reliability of presented outcomes.