Event‐triggered disturbance rejection control for Markov jump systems: A GA‐optimized approach

Abstract

This paper investigates the event‐triggered disturbance rejection control problem for discrete‐time Markov jump systems by means of genetic algorithms. Firstly, an extended state observer is developed to estimate the system states and disturbances and construct the event‐triggered disturbance rejection controller. With resort to Lyapunov theory, the uniform ultimate boundedness of both estimated errors and states is guaranteed. The disturbance rejection performance is also analyzed. The genetic algorithm is adopted to avoid conservatism in solving the given nonlinear conditions and achieve a meaningful optimization arising from realizing better system performance. The designed approach not only realizes a trade‐off between the bounds of estimated errors and states but also rejects the disturbance. Finally, an example is given to illustrate the effectiveness of the proposed approach.