基于ADP的非对称约束系统动态事件触发方法OA
ADP-based Dynamic Event-triggering Method for Asymmetric Constrained Systems
本文提出一种基于自适应动态规划的动态事件触发方法(DEM),用于解决具有状态与控制双重非对称约束的非线性连续时间系统最优控制问题.首先,利用非线性映射函数将非对称约束系统的控制问题转化为无约束形式.然后,设计一种静态事件触发方法(SEM),其中触发条件仅与当前状态相关.进一步,开发一种依赖额外内部动态变量的 DEM,其触发条件也与系统历史信息相关.事实上,DEM 是 SEM 的进阶方法.理论分析证实 DEM 在确保系统性能的情况下,能够进一步节省计算和网络资源.最后,介绍基于神经网络的实现方法.在无人水面艇仿真实验环境下,该方法的有效性得到了验证.
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.
薛珊;赵宁;张卫东
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
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
adaptive dynamic programmingadaptive critic designsneural networksevent-triggering methoddy-namic event-triggering method
《自动化学报》 2026 (6)
1209-1220,12
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)
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