Incentive feedback Stackelberg strategy for stochastic systems with state-dependent noise |
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| Institution: | 1. School of Mathematics and Statistics, Shandong University of Technology, Zibo 255000, China;2. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590, China;1. College of Automation, Chongqing University, Chongqing, 400044, China;2. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, China;1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China;2. Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, University of Electronic and Technology of China, Chengdu 611731, China;3. Department of Computer Science and Technology, Faculty of Science and Engineering, University of Hull, HU6 7RX, UK;1. School of Mathematical Sciences, University of Jinan, Jinan 250022, China;2. College of Information Science and Engineering, Shandong Agricultural University, Tai’an 271018, China;1. College of Sciences, Northeastern University, Shenyang, Liaoning province, 110819, PR China;2. The State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning province, 110819, PR China;1. School of Mathematics, Shanghai University of Finance and Economics, Shanghai, 200433, Shanghai, China;2. School of Applied Mathematics, Nanjing University of Finance and Economics, Nanjing, 210023, Jiangsu, China;3. MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410081, Hunan, China;4. Key Laboratory of Control and Optimization of Complex Systems, Hunan Normal University, College of Hunan Province, Changsha 410081, China |
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| Abstract: | This paper designs an incentive strategy for a class of stochastic Stackelberg games in finite horizon and infinite horizon, respectively. The obtained incentive Stackelberg strategy works well in the sense that the leader will get his desired solution in the end. Different from the existing works, the state-dependent noise is considered in the design of the incentive Stackelberg strategy. Moreover, the mean-square stabilization can be guaranteed by the follower. The algorithm procedure is put forward to obtain effectively the incentive feedback Stackelberg strategy in infinite horizon. Finally, two examples are given to shed light on the effectiveness of the proposed algorithm procedure. |
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