Static Output-Feedback Incentive Stackelberg Game for Discrete-Time Markov Jump Linear Stochastic Systems With External Disturbance

Abstract

This letter investigates an infinite-horizon incentive Stackelberg game for discrete-time linear stochastic systems subject to Markov jump parameters and external disturbance by means of static output-feedback (SOF). In contrast to the existing studies, players can only have access to local output information in designing their incentive Stackelberg strategies with H _∞ constraint. It is shown that the incentive Stackelberg strategy set is obtained by solving a set of higher-order cross-coupled Lyapunov type equations. As another important contribution, a numerical algorithm is proposed based on the coordinate descent method that guarantees local convergence. A numerical example demonstrates the existence of the SOF incentive Stackelberg strategy set and the effectiveness of the proposed algorithm.