Asynchronous fault detection filtering for piecewise homogenous Markov jump linear systems via a dual hidden Markov model

This work investigates the asynchronous fault detection filtering issue for discrete-time piecewise homogeneous Markov jump systems. By resorting to a dual hidden Markov model, an asynchronous fault detection filter is presented which can follow up the system modes. Utilizing the stochastic Lyapunov function approach, sufficient conditions are devised to make the resultant Markov jump systems be stochastically stable and hold a specified H-infinity performance level. Finally, a real-time experiment based on the automotive electronic throttle body is employed to validate the devised asynchronous fault detection filter which can find the faults after the occurrences in the case of no false alarm. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This work investigates the issue of asynchronous fault detection filtering for discrete-time piecewise homogeneous Markov jump systems. A novel asynchronous fault detection filter is proposed and validated through real-time experiments.