非参数不确定多智能体系统一致性误差跟踪学习控制  

Consensus-error-tracking learning control for nonparametric uncertain multi-agent systems

作　　者：严求真[1,2] 孙明轩[1] 李鹤[1] 

机构地区：[1]浙江工业大学信息工程学院,浙江杭州310023 [2]浙江水利水电学院信息工程学院,浙江杭州310018

出　　处：《控制理论与应用》2016年第6期793-799,共7页Control Theory & Applications

基　　金：国家自然科学基金项目(61174034;61374103;6157330)资助~~

摘　　要：针对一类在有限时间区间上执行重复任务的主-从型非参数不确定多智能体系统,提出一致性误差跟踪学习控制方法,用于解决在任意初始误差情形下的一致性问题.根据Lyapunov综合方法设计控制器,经过足够多次迭代后,藉由从智能体的一致性误差在整个作业区间上完全跟踪对应的期望一致性误差轨迹,实现各从智能体在预设的部分作业区间上对主智能体的零误差轨迹跟踪.采用鲁棒策略与学习策略相结合的手段处理非参数不确定性,利用双曲正切函数设计反馈项补偿随迭代次数变化但有界的不确定性.仿真结果表明了该控制方案的有效性.This paper presents a consensus-error-tracking iterative learning control method to tackle the consensus problem for a class of leader-following non-parametric uncertain multi-agent systems, which perform a given repetitive task over a finite interval with arbitrary initial error. The iterative learning controllers are designed by applying Lyapunov synthesis. As the iteration increases, each following multi-agent＇s consensus-error can track its desired consensus-error trajectory, and the all following multi-agents＇ states perfectly track the leader＇s state on the specified interval. The robust learning technique is applied to deal with the nonparametric uncertainties, and the hyperbolic tangent function is used to design feedback terms, in order to compensate the cycle-varying but bounded uncertainty. Numerical results demonstrate the effectiveness of the learning control scheme.

关 键 词：多智能体系统 迭代学习控制 一致性算法 初值问题 非参数不确定性 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP13[自动化与计算机技术—控制科学与工程]