Noncooperative Model Predictive Game With Markov Jump Graph  

作　　者：Yang Xu Yuan Yuan Zhen Wang Xuelong Li 

机构地区：[1]School of Astronautics,Northwestern Polytechnical University,Xi’an 710072,China [2]School of Computer Science and Center for Optical Imagery Analysis and Learning,Northwestern Polytechnical University,and also with the School of Cybersecurity,Northwestern Polytechnical University,Xi’an 710072,China [3]School of Artificial Intelligence,Optics and Electronics(iOPEN),Northwestern Polytechnical University,and also with the Key Laboratory of Intelligent Interaction and Applications,Northwestern Polytechnical University,Ministry of Industry and Information Technology,Xi’an 710072,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2023年第4期931-944,共14页自动化学报（英文版）

基　　金：This work was supported by the National Natural Science Foundation of China(62122063,62073268,U22B2036,11931015);the Young Star of Science and Technology in Shaanxi Province(2020KJXX-078);the National Science Fund for Distinguished Young Scholars(62025602);the XPLORER PRIZE。

摘　　要：In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the reality,the state and input constraints have been considered along with the external disturbances.An iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed manner.Sufficient conditions are established to guarantee the convergence of the proposed algorithm.In addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying MPSs.Finally,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.

关 键 词：Markov jump graph model predictive control(MPC) multi-player systems(MPSs) noncooperative game ε-Nash equilibrium 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]