Event-triggered optimal control scheme for discrete-time nonlinear zero-sum games

被引：1
|
作者：
Zhang X. [1 ]
Bo Y.-C. [1 ]
Cui L.-L. [2 ]
机构：
[1] College of Information and Control Engineering, China University of Petroleum, Qingdao, 266580, Shandong
[2] Sofeware College, Shenyang Normal University, Shenyang, 110034, Liaoning
来源：
Zhang, Xin (zhangxin@upc.edu.cn) | 2018年 / South China University of Technology卷 / 35期
基金：
中国国家自然科学基金;
关键词：
Adaptive dynamic programming; Event-triggered; Game theory; Optimal control;
D O I：
10.7641/CTA.2018.70791
中图分类号：
学科分类号：
摘要：
In order to reduce the network communication and controller execution frequency while guarantee a desired control performance, an event-triggered optimal control scheme is proposed for solving the optimal control pair of discrete time nonlinear zero-sum games in this paper. Firstly, an event-triggered condition with new event-triggered threshold is designed. The expression of the optimal control pair is obtained based on the Bellman optimality principle. Then, a single network value iteration algorithm is proposed to solve the optimal value function in this expression. A neural network is used to construct the critic network. Novel weight update rule of the critic network is derived. Through the iteration between the critic network, the control policy and the disturbance policy, the optimal value function and the optimal control pair can be solved. Further, the Lyapunov theory is used to prove the stability of the event-triggered closed-loop system. Finally, the event-triggered optimal control mechanism is applied to two examples to verify its effectiveness. © 2018, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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页码：619 / 626
页数：7
相关论文
共 18 条
  • [1] Fu Y., Chai T., Online solution of two-player zero-sum games for linear systems with unknown dynamics, Control Theory & Applications, 32, 2, pp. 196-201, (2015)
  • [2] Yves A., Perez V., Iterative strategies for solving linearized discrete mean field games systems, Netw Heterog Media, 7, 2, pp. 197-217, (2012)
  • [3] Fu Y., Fu J., Chai T., Robust adaptive dynamic programming of two-player zero-sum games for continuous-time linear systems, IEEE Transactions on Neural Networks and Learning Systems, 26, 12, pp. 3314-3319, (2015)
  • [4] Astrom K.J., Bernhardsson B.M., Comparison of Riemann and Lebesgue sampling for first order stochastic systems, Proceedings of the 41st IEEE Conference on Decision Control, 2, pp. 2011-2016, (2002)
  • [5] Heemeles W., Donkers M., Teel A., Periodic event-triggered control for linear systems, IEEE Transactions on Automatic Control, 58, 4, pp. 847-861, (2013)
  • [6] Liang Y., Qi G., Li Y., Et al., Design and application of event-triggered mechanism for a kind of optical-electronic tracking system, Control Theory & Applications, 34, 10, pp. 1328-1338, (2017)
  • [7] Sahoo A., Xu H., Jagannathan S., Neural network-based event triggered state feedback control of nonlinear continuous-time systems, IEEE Transactions on Neural Networks and Learning Systems, 27, 3, pp. 497-509, (2016)
  • [8] Vamvoudakis K.G., Event-triggered optimal adaptive control algorithm for continuous-time nonlinear systems, IEEE/CAA Journal of Automatica Sinica, 1, 3, pp. 282-293, (2014)
  • [9] Zhang Q., Zhao D., Zhu Y., Event-triggered H<sub>∞</sub> control for continuous-time nonlinear system via concurrent learning, IEEE Transactions on Systems, Man, and Cybernetics, 47, 7, pp. 1071-1081, (2017)
  • [10] Werbos P.J., Approximate dynamic programming for real-time control and neural modeling, Handbook of Intelligent Control: Neural, Fuzzy and Adaptive Approaches, (1992)
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