Leader-following多智能体网络分布式编队控制

针对多智能体固定拓扑网络,考虑无时延和有时延两种情况,研究了多智能体网络的分布式编队控制协议.首先,针对无通信时延的多智能体网络,提出了分布式编队控制协议,利用Lyapunov稳定理论,给出了协议有效的充分条件.然后,考虑时变通信时延,利用Lyapunov-Krasovskii函数证明了协议的有效性.最后,利用仿真实验证明了所设计协议的有效性.本文的创新点是对二阶多智能体网络设计分布式编队控制协议时考虑了速度一致性.     

基于终端滑模控制的多智能体系统有限时间跟踪控制

针对有向拓扑结构下带领导者的非线性二阶多智能体系统,基于终端滑模控制策略,研究其有限时间一致性跟踪问题;利用快速积分型终端滑模控制理论与有限时间稳定性理论,设计了一类分布式有限时间一致跟踪控制协议,以确保多智能体系统中跟随者对动态领导者的跟踪。提出的控制协议可以使多智能体系统的状态在有限时间内到达并停留在设计的滑模面上,并且能有效削弱抖振。通过数值仿真,验证了所获得的理论结果的有效性。     

Leader-following consensus protocols for formation control of multi-agent network

Two protocols are presented,which can make agents reach consensus while achieving and preserving the desired formation in fixed topology with and without communication timedelay for multi-agent network.First,the protocol without considering the communication time-delay is presented,and by using Lyapunov stability theory,the sufficient condition of stability for this multi-agent system is presented.Further,considering the communication time-delay,the effectiveness of the protocol based on Lyapunov-Krasovskii function is demonstrated.The main contribution of the proposed protocols is that,as well as the velocity consensus is considered,the formation control is concerned for multi-agent systems described as the second-order equations.Finally,numerical examples are presented to illustrate the effectiveness of the proposed protocols.     

Leader-following coordination of multi-agent systems with information feedback

Based on the strategy of information feedback from followers to the leader, flocking control of a group of agents with a leader is studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion. The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers’ faults. The results of simulation are provided to illustrate that information feedback can improve the performance of the system.     

具有和不具有非线性动态的二阶时滞多智能体系统的领导跟随一致性(英文)

研究了带有时滞的二阶多智能体系统的领导跟随一致性问题.所给定的领导者不仅位置和速度保持变化,而且带有时滞.首先,为了跟踪这样一个具有非线性动态的领导者,对于每一个智能体给出了基于邻域的分布式控制器,基于Lyapunov-Razumikhin理论,获得了二阶多智能体系统达到领导跟随一致性的充分条件.另外,讨论了领导者和每个智能体都不具有非线性动态的一致性问题,得到了使得多智能体系统达到一致性的充分条件.最后,给出的仿真结果表明了所获定理的有效性.     

具有采样时延的多智能体系统的一致性跟踪

针对存在采样时延的多智能体系统的采样控制问题,提出了一类基于领导-跟随模型的有界一致性跟踪协议.运用时延分解技术、增广矩阵方法和频域分析方法,得到了确保系统实现有界一致性跟踪的充要条件,系统的收敛性由网络拓扑结构、采样周期及采样时延等因素决定.通过数字仿真,进一步验证了所提出协议的有效性.     

分布式HDP领导-跟随者系统最优一致控制研究

为研究行为未知的非线性多智能体系统领导-跟随者最优一致控制问题,针对智能体动态方程未知的情况,设计神经网络辨识器学习智能体动力学行为;构造以多智能体系统局部误差为输入的性能指标函数,将多智能体系统领导-跟随者一致性问题转换为求解智能体局部性能指标函数最优值的优化控制问题;结合自适应动态规划思想设计分布式迭代算法求解该优化问题,并讨论了算法的收敛性;设计基于神经网络的评价-执行结构分布式控制器来近似局部性能指标函数,通过神经网络学习迭代寻找局部性能指标函数的最优解,实现多智能体系统的最优一致控制策略。设计的分布式控制器能够根据智能体状态数据自适应产生控制策略,使多智能体系统趋于一致。