基于平行控制的离散非线性系统的事件触发近似最优控制

doi:10.11959/j.issn.2096-6652.202142

智能科学与技术学报 ›› 2021, Vol. 3 ›› Issue (4): 435-443.doi: 10.11959/j.issn.2096-6652.202142

• 专栏：基于数据的学习与优化 • 上一篇下一篇

基于平行控制的离散非线性系统的事件触发近似最优控制

廖泽华¹^,², 梁子钰¹^,³, 周天民¹, 卢经纬¹^,², 魏庆来¹^,²

¹ 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
² 中国科学院大学人工智能学院，北京 100049
³ 天津大学智能电网教育部重点实验室，天津300072

修回日期:2021-11-01 出版日期:2021-12-15 发布日期:2021-12-01
作者简介:廖泽华（1994- ），男，中国科学院大学人工智能学院博士生，主要研究方向为自适应动态规划、强化学习、最优控制
梁子钰（1997- ），女，天津大学智能电网教育部重点实验室硕士生，主要研究方向为配电系统规划与运行
周天民（1990- ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室博士后，主要研究方向为复杂系统建模与调控、自适应动态规划与强化学习、神经网络，以及智能控制与决策方法在工程、社会经济系统中的应用等
卢经纬（1990- ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室博士生，主要研究方向为最优控制、自适应动态规划和强化学习
魏庆来（1979- ），男，博士，中国科学院自动化研究所研究员，复杂系统管理与控制国家重点实验室副主任，中国自动化学会理事，国家自然科学基金优秀青年科学基金获得者，担任IEEE/CAA Journal of Automatica Sinica、Neurocomputing、IEEE Transactions on Neural Networks and Learning Systems、《自动化学报》《智能科学与技术学报》等多个学术期刊副主编或编委。在自适应动态规划自学习最优控制领域，主持科研项目20项，其中省部级以上8项，发表SCI论文120余篇，出版专著3部，授权专利10余项，连续两年（2018年和2019年）入选科睿唯安全球高被引科学家，2017年获得中国自动化学会自然科学奖一等奖、中国自动化学会杨嘉墀科技奖，2019 年获得中国产学研合作创新奖，2020 年获得中国发明协会发明创业奖成果奖二等奖
基金资助:
国家自然科学基金资助项目(62073321)

Parallel control-based event-driven approximate optimal control of discrete-time nonlinear systems

Zehua LIAO¹^,², Ziyu LIANG¹^,³, Tianmin ZHOU¹, Jingwei LU¹^,², Qinglai WEI¹^,²

¹ The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100086, China
² School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
³ Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

Revised:2021-11-01 Online:2021-12-15 Published:2021-12-01
Supported by:
The National Natural Science Foundation of China(62073321)

摘要/Abstract

摘要：

针对离散非线性系统提出了一种基于平行控制的事件触发近似最优控制方法。首先，基于时间触发的最优值函数和最优控制律，提出了一种新型的触发条件，并基于李雅普诺夫方法证明了闭环系统的渐近稳定性。其次，为了实施设计的触发条件，提出了一种采用神经网络和自适应动态规划技术的平行控制方法，以预测系统的下一步状态，并获得最优值函数和最优控制律。最后，通过仿真实验验证了所提方法的有效性。

关键词: 事件触发控制, 非线性最优控制, 平行控制, 自适应动态规划

Abstract:

A parallel control-based event-driven approximate optimal control method was proposed for discrete-time nonlinear systems.Firstly, based on the time-triggered optimal value function and optimal control law, a novel triggering condition was developed and the asymptotic stability of the closed-loop system was proved based on the Lyapunov method.Secondly, a parallel control method using neural networks and adaptive dynamic programming techniques was proposed to predict the next state of the system and to obtain the optimal value function and control law.Finally, the effectiveness of the developed method was validated by numerical examples.

Key words: event-driven control, nonlinear optimal control, parallel control, adaptive dynamic programming

中图分类号:

TP273

廖泽华, 梁子钰, 周天民, 等. 基于平行控制的离散非线性系统的事件触发近似最优控制[J]. 智能科学与技术学报, 2021, 3(4): 435-443.

Zehua LIAO, Ziyu LIANG, Tianmin ZHOU, et al. Parallel control-based event-driven approximate optimal control of discrete-time nonlinear systems[J]. Chinese Journal of Intelligent Science and Technology, 2021, 3(4): 435-443.

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基于平行控制的离散非线性系统的事件触发近似最优控制

Parallel control-based event-driven approximate optimal control of discrete-time nonlinear systems

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