未知大规模互联系统在线分散式动态事件触发控制

何怡睿; 苏涵光; 张化光; 栾鑫洋

doi:10.16383/j.aas.c240262

未知大规模互联系统在线分散式动态事件触发控制

doi: 10.16383/j.aas.c240262 cstr: 32138.14.j.aas.c240262

1.
东北大学信息科学与工程学院沈阳 110819

基金项目: 国家自然科学基金(62373091, 62103087, 62203311, U22A2055), 中国博士后科学基金(2024T170112, 2021M690567), 国家重点研发计划项目(2018YFA0702200), 中央高校基本科研业务费(N2104016, N2304009), 辽宁省自然科学基金联合基金(2023-MSBA-082), 辽宁省综合能源优化与安全运行重点实验室, 中国工程院院地合作咨询项目(2023-DFZD-60, 2023-DFZD-60-03)资助

详细信息

作者简介:
何怡睿：东北大学信息科学与工程学院本科生. 主要研究方向为大规模系统的最优控制, 事件触发, 自适应动态规划. E-mail: 20212366@stu.neu.edu.cn

苏涵光：东北大学信息科学与工程学院副教授. 主要研究方向为综合能源系统及其优化控制, 自适应动态规划, 人工智能技术. 本文通信作者. E-mail: suhanguang@ise.neu.edu.cn

张化光：东北大学信息科学与工程学院教授, 教育部长江学者, IEEE Fellow. 主要研究方向为自适应动态规划, 模糊控制, 网络控制, 混沌控制, 能源互联网. E-mail: hgzhang@ieee.org

栾鑫洋：东北大学信息科学与工程学院博士研究生. 2024年获东北大学硕士学位. 主要研究方向为大规模系统的最优控制, 综合能源系统, 自适应动态规划. E-mail: luanxinyang_daria@163.com

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出版历程
- 收稿日期: 2024-05-13
- 录用日期: 2024-08-27
- 网络出版日期: 2024-11-07

Online Decentralized Dynamic Event-triggered Control of Unknown Large-scale Interconnected Systems

1.
College of Information Science and Engineering, Northeast ern University, Shenyang 110819

Funds: Supported by National Natural Science Foundation of China (62373091, 62103087, 62203311, U22A2055), China Postdoctoral Science Foundation (2024T170112, 2021M690567), National Key R & D Program of China (2018YFA0702200), the Fundamental Research Funds for the Central Universities (N2104016, N2304009), Natural Science Foundation of Liaoning Province (2023-MSBA-082), Key Laboratory of Integrated Energy Optimization and Secure Operation of Liaoning Province, and China Academy of Engineering institute of Land Cooperation Consulting Project (2023-DFZD-60, 2023-DFZD-60-03)

More Information

Author Bio:
HE Yi-Rui　Undergraduate student at the School of Information Science and Engineering, Northeastern University. His research interest covers optimal control of large-scale systems, event trigger, and adaptive dynamic programming

SU Han-Guang　Associate professor at the School of Information Science and Engineering, Northeastern University. His research interest covers integrated energy systems and their optimization control, adaptive dynamic programming, and artificial intelligence technologies. Corresponding author of this paper

ZHANG Hua-Guang　Professor at the School of Information Science and Engineering, Northeastern University. Changjiang Scholars of Ministry of Education and IEEE Fellow. His research interest covers adaptive dynamic programming, fuzzy control, network control, chaos control, and energy internet

LUAN Xin-Yang　Ph.D. candidate at the School of Information Science and Engineering, Northeastern University. She received her master degree from Northeastern University in 2024. Her research interest covers optimal control of large-scale systems, integrated energy systems, and adaptive dynamic programming

摘要

摘要: 针对一类系统动态未知且受互联项影响的非线性互联大规模系统, 提出一种新的在线分散式动态事件触发控制(Dynamic event-triggered control, DETC)方案. 首先, 构建基于神经网络的辨识器来重构互联系统的未知内部动态. 其次, 使用自适应评判网络在事件触发机制下学习近似最优控制策略. 在所设计的动态事件触发控制机制下, 各子系统独立地设计自己的控制策略, 且各控制策略的更新是异步进行的. 也就是说, 各个分散式事件触发条件和控制器仅依赖于各自子系统的局部状态信息, 而无需频繁获取相邻子系统的信息, 从而规避通过通信网络在子系统间传递状态信息的需求. 然后, 借助李雅普诺夫稳定性定理, 从理论上证明所提出的闭环控制系统状态和评判网络权值估计误差都是最终一致有界的. 最后, 通过一个数值仿真示例和一个实际工程示例验证所提出的动态事件触发控制方法的有效性和实用性.
- 自适应动态规划 /
- 动态事件触发控制 /
- 大规模系统 /
- 控制受限
Abstract: This article introduces a novel online decentralized dynamic event-triggered control (DETC) scheme designed for a class of nonlinear interconnected large-scale systems whose system dynamics are unknown and influenced by interconnections. Firstly, we utilize a neural network-based identifier to reconstruct these unknown internal dynamics. Secondly, we develop an adaptive critic network to learn the approximate optimal control policies under a dynamic event-triggered mechanism. In this mechanism, the control policies for each subsystem are designed independently, and the update of the control policies is completed asynchronously. In other words, each decentralized event trigger condition and controller only rely on the local state information of their respective subsystems, and there is no need to frequently obtain information from adjacent subsystems, thus circumventing the need to transfer state information between subsystems through communication networks. Furthermore, by employing Lyapunov theorem, we demonstrate that both the closed-loop control system states and the critic network weights estimation errors are ultimately uniformly bounded. Finally, the effectiveness and feasibility of the developed dynamic event-triggered control method are validated through both a numerical example and a real-world application.
- Adaptive dynamic programming (ADP) /
- dynamic event-triggered control (DETC) /
- large-scale systems /
- control constraint

HTML全文

图 1 三阶互联系统(69)控制过程

Fig. 1 The three-order interconnected systems (69)

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图 2 三阶互联系统(69)控制过程

Fig. 2 The three-order interconnected systems (69)

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图 3 三阶互联系统(69)控制过程

Fig. 3 The three-order interconnected systems (69)

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图 4 三阶互联系统(69)子系统1、2和3的触发时刻

Fig. 4 For the three-order interconnected systems (69), the triggering instants for subsystems 1, 2 and 3

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图 5 三机互联电力系统(70)控制过程

Fig. 5 The three-machine power interconnected systems (70)

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图 6 三机互联电力系统(70)控制过程

Fig. 6 The three-machine power interconnected systems (70)

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图 7 三机互联电力系统(70)控制过程

Fig. 7 The three-machine power interconnected systems (70)

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图 8 三机互联电力系统(70)子系统1、2和3的触发时刻

Fig. 8 For the three-machine power interconnected systems (70), the triggering instants for subsystems 1, 2 and 3

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