Adaptive optimal containment control for nonlinear multi-agent systems with time-varying output constraints
ZHANG Tian-ping
LIU Tao
ZHANG En-ze
Abstract：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 apply-ing 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.
Keywords：adaptive dynamic programmingintegral reinforcement learningoptimal controldynamic surface controlintegral barrier Lyapunov functionmulti-agent systems
Publication Date：2024-10-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：14( 1899-1912 )