Event-triggered fault detection for nonlinear semi-Markov jump systems based on double asynchronous filtering approach

The event-triggered fault detection problem for nonlinear semi-Markov jump systems constructed by Takagi–Sugeno fuzzy approach is studied in this paper. Owing to that the premise variables and the modes are usually mismatched for both the filter and the plant in actual network environment, i.e., the double asynchronous phenomenon, a novel double asynchronous fault detection filter is designed to take the place of the traditional filter and tackle the fault detection problem for fuzzy semi-Markov jump systems. Particularly, the event-triggered scheme is considered to reduce the waste of communication resources, which gives rise to the premise variables asynchronous phenomenon for the plant and the filter. The modes information of the fuzzy semi-Markov jump systems is not always instantaneously accessible, which leads to the mode asynchronous phenomenon for the plant and the filter. This mode asynchronous phenomenon is described by a hidden semi-Markov model. Based on Lyapunov stability theory, the sufficient conditions are developed to ensure that the system not only is stochastically stable and meets an H∞ performance, but also can make sure that the filter gains could be captured. Finally, an illustrative tunnel diode circuit example is provided to show the effectiveness of proposed approach.