An event-triggered STF approach to fault detection for nonlinear discrete time systems

Abstract

Aiming to fault detection (FD) for nonlinear systems, a novel event-triggered strong tracking filter (STF) approach is proposed in this paper. An STF has been applied as an event-triggered residual generator as well as the generated residual signals have been entirely decoupled from the event-triggered transmission errors. Then, designing the residual generator is converted into finding a filter matrix that makes the state estimation error covariance minimized. Besides, a new residual evaluation strategy is presented. It is accepted that designing the filter matrix is independent from choosing the value of event. Finally, a simulation experiment is carried out on a three-tank system to show the effectiveness of the suggested FD strategy.