迭代学习在多智能体编队中的控制研究

Multi-agent Formation in the Iterative Learning Control

针对具有控制时延的非线性多智能体系统模型,设计了一种能够实现其稳定编队的迭代学习控制算法.首先,建立单个智能体的动态特性,根据多智能体的拓扑连接结构,将多智能体编队控制问题转化为跟踪问题.其次,针对每个智能体设计形式统一的迭代学习控制器,根据每个智能体不同的动态特性,选取合适的学习增益矩阵.最后,基于λ范数理论证明了算法的收敛性.由于该迭代学习控制算法放宽了对迭代初值的限定,使其达到在任意常值初态条件下的稳定控制,从而满足了各个智能体在初始位置随机分布时的编队控制要求.仿真结果证明了文中所给算法的有效性.

For the nonlinear multi-agent systems with delay,an iterative learning control law was designed in order to achieve the stable formation of multi-agent systems.The dynamic characteristics of a single agent were established,and the problem of formation control of multi-agent was transformed into a tracking problem according to the topology structure of multi-agent.A unified iterative learning controller was designed for each agent.According to the different dynamic characteristics of each agent,a suitable learning gain matrix was selected.Then the convergence of the proposed iterative learning law was proved based on theλnorm theory.Due to the relaxation of initial value in the iterative learning control algorithm,the stability of the control can be achieved in any constant initial condition.The algorithm proposed can meet the formation control requirement for each agent having random initial position.Finally,the simulation results were given to illustrate the effectiveness of the proposed method.