A new insight on the event‐triggered state feedback control for Markov jump systems

Abstract

The event‐triggered control of Markov jump systems has attracted more and more interest in field control. However, the problem of how to design a transition probability‐dependent event‐triggered mechanism and controller has not been fully considered. This paper investigates the problem of event‐triggered control for Lipschitz nonlinear Markov jump systems. Through Taylor series expansion, a linear auxiliary system is constructed to obtain the approximate state, whose system matrices are described by the probability‐weighted matrices of nonlinear Markov jump systems. By redefining the measurement error as the difference between the current state and the approximate state, a probability‐dependent event‐triggered mechanism is designed for Markov jump systems. The effectiveness of the developed approach is illustrated by two comparison examples.