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基于ADP的非对称约束系统动态事件触发方法

薛珊 赵宁 张卫东

自动化学报2026,Vol.52Issue(6):1209-1220,12.
自动化学报2026,Vol.52Issue(6):1209-1220,12.DOI:10.16383/j.aas.c250544

基于ADP的非对称约束系统动态事件触发方法

ADP-based Dynamic Event-triggering Method for Asymmetric Constrained Systems

薛珊 1赵宁 2张卫东3

作者信息

  • 1. 海南大学信息与通信工程学院 海口 570228||安徽大学人工智能学院 合肥 230601||海洋智能系统教育部工程研究中心 海口 570228
  • 2. 海南大学信息与通信工程学院 海口 570228||海洋智能系统教育部工程研究中心 海口 570228
  • 3. 海南大学信息与通信工程学院 海口 570228||海洋智能系统教育部工程研究中心 海口 570228||上海交通大学自动化与智能感知学院 上海 200240
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摘要

Abstract

In this paper,an adaptive dynamic programming-based dynamic event-triggering method(DEM)is de-veloped to solve the optimal control problem of nonlinear continuous-time systems with asymmetric constraints for both state and control.First,a nonlinear mapping function is used to transform the control problem of asymmetric constrained systems into an unconstrained form.Then,a static event-triggering method(SEM)is designed,where triggering conditions are only associated with the current state.Based on the SEM,a DEM that relies on an addi-tional internal dynamic variable is developed,whose triggering condition is also related to the system historical in-formation.In fact,the DEM is an advanced method of the SEM.Theoretical analysis proves that the DEM can fur-ther save computational and network resources while ensuring system performance.Finally,the neural network-based implementation is presented.The effectiveness of this method has been verified in the simulation experiment environment of the unmanned surface vehicle.

关键词

自适应动态规划/自适应评价设计/神经网络/事件触发方法/动态事件触发方法

Key words

adaptive dynamic programming/adaptive critic designs/neural networks/event-triggering method/dy-namic event-triggering method

引用本文复制引用

薛珊,赵宁,张卫东..基于ADP的非对称约束系统动态事件触发方法[J].自动化学报,2026,52(6):1209-1220,12.

基金项目

国家自然科学基金(U2141234,U24A20260,62403173),海南省自然科学基金(725RC724),海南省高等教育科研资助项目(Hnky2025ZD-2),中国国家科技重大专项(2022ZD0119900),海南省科技专项(ZDYF2024GXJS003),海南大学科研基金(XJ2400000440)资助 Supported by National Natural Science Foundation of China(U2141234,U24A20260,62403173),Hainan Provincial Natural Science Foundation(725RC724),Hainan Higher Education Sci-entific Research Funding Project(Hnky2025ZD-2),National Sci-ence and Technology Major Project of China(2022ZD0119900),Hainan Provincial Science and Technology Special Fund(ZDYF2024 GXJS003),and Scientific Research Fund of Hainan University(XJ2400000440) (U2141234,U24A20260,62403173)

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