摘要
本文对具有时变输出约束和未建模动态的不确定严格反馈非线性多智能体系统,提出了一种最优包含控制方法.利用一种新型积分型障碍Lyapunov函数处理输出约束,利用动态信号处理未建模动态,利用动态面控制方法设计前馈控制器,结合自适应动态规划和积分强化学习方法设计最优反馈控制器,利用神经网络在线逼近相应代价函数,并设计权重更新律.理论分析证明了所有跟随者的输出收敛到领导者生成的凸包中,全部跟随者组成的闭环系统是半全局一致最终有界的,同时,跟随者的输出保持在给定的约束集中,代价函数达到最小.仿真结果验证了所提出方法的有效性.
In this paper,an optimal containment control method is proposed for uncertain strict-feedback nonlinear multi-agent systems with time-varying output constraints and unmodeled dynamics.A new type integral barrier Lyapunov function is utilized to handle output constraints.A dynamical signal is applied to dispose of unmodeled dynamics.The dynamic surface control is used to design feedforward controller.The optimal feedback controller is constructed by applying adaptive dynamic programming and integral reinforcement learning techniques in which neural networks are utilized to approximate the relevant cost functions online with established weight updating laws.By theoretical analysis,the outputs of all followers converge to the convex hull spanned by all leaders,and the closed-loop control system composed of the whole followers is proved to be cooperative semi-globally uniformly ultimately bounded(SGUUB).In the mean time,the outputs maintain in the provided constraint sets and cost functions achieve minimization.A simulation example is presented to illustrate the feasibility of the developed approach.
作者
张天平
刘涛
章恩泽
ZHANG Tian-ping;LIU Tao;ZHANG En-ze(Department of Automation,College of Information Engineering,Yangzhou University,Yangzhou Jiangsu 225127,China)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2024年第10期1899-1912,共14页
Control Theory & Applications
基金
国家自然科学基金项目(62073283,62203381)资助.
