有向图中网络Euler-Lagrange系统的自适应协调跟踪

基于一致性理论, 在有向图中研究网络 Euler-Lagrange 系统的协调跟踪控制. 所有跟随智能体的动力学模型均为 Euler-Lagrange 方程. 在仅有部分跟随智能体能获取领航智能体信息的情形下, 同时考虑系统模型的参数不确定性, 设计分布式自适应控制律实现所有跟随智能体对领航智能体的跟踪. 针对领航智能体的运动状态, 考虑以下两种情形: 1) 领航智能体为固定点; 2) 领航智能体为动态点. 对第一种情形, 设计的控制律使得所有跟随智能体渐近交会于固定点; 对第二种情形, 首先对每个跟随智能体设计分布式连续估计器, 然后提出了分布式自适应控制律. 当每个跟随智能体均能获取领航智能体的加速度信息时, 设计的控制律能实现对领航智能体的渐近跟踪, 当跟随智能体不能获取领航智能体的加速度信息时, 跟踪误差是有界的. 最后通过仿真分析验证设计的控制算法是合理有效的.     

线性多智能体系统在固定和切换拓扑下的领航跟随控制

研究线性多智能体系统的领航跟随一致性问题. 假设每个多智能体系统只能得到其邻域的输出测量信息, 在此条件下, 讨论多智能体在有向固定网络拓扑和无向切换网络拓扑两种情况下的一致性问题. 针对这两种情况, 提出含有一种分布式观测器的一致性控制算法. 应用Lyapunov 稳定性理论证明了若单个多智能体系统是可镇定和可检测的, 且网络连接拓扑只需满足简单的结构, 则系统能够达到领航跟随一致性. 仿真结果验证了理论分析的正确性.     

考虑状态约束的航天器编队分布式姿态协同跟踪控制

针对有向通信拓扑结构下的航天器编队姿态协同控制问题,提出一种基于反步法的分布式姿态协同跟踪控制律.在仅有部分跟随航天器可以获取动态领航航天器信息的情况下,利用多层神经网络的逼近特性对系统的非线性不确定性进行估计.同时,考虑到航天器编队的姿态协同跟踪控制性能,构造Barrier Lyapunov函数,使得状态变量保持在预设的约束区间内,进而实现对姿态跟踪误差的约束.根据代数图论和Lyapunov理论,证明跟随航天器的姿态跟踪误差最终有界.仿真分析表明了所提出控制方法的有效性.     

多航天器系统分布式有限时间姿态协同跟踪控制

基于一致性算法, 在有向通讯拓扑下, 研究存在状态约束的多航天器系统分布式有限时间姿态协同跟踪控制问题. 在仅有部分跟随航天器可以获取领航航天器状态, 并且跟随航天器之间存在不完全信息交互的情形下, 设计了分布式快速终端滑模面, 提出了不依赖于模型的分布式有限时间姿态协同跟踪控制律. 根据有限时间Lyapunov 稳定性定理, 证明了系统的状态在有限时间内收敛于领航航天器状态的小邻域内. 最后通过仿真算例验证了所提出算法的有效性.

     

非仿射非线性多智能体系统迭代学习一致跟踪

为了解决非仿射非线性多智能体系统在给定时间区间上一致性完全跟踪问题,基于迭代学习控制方法设计一种分布式一致性跟踪控制算法.首先,由引入的虚拟领导者与所有跟随者组成多智能体系统的通信拓扑,其中虚拟领导者的作用是提供期望轨迹.然后,在只有部分跟随者能够获得领导者信息的条件下,利用每个跟随者及其邻居的跟踪误差构造每个跟随者的迭代学习一致性跟踪控制器.同时采用中值定理将非仿射非线性多智能体系统转化仿射形式,并基于压缩映射方法证明所提算法的收敛性,给出算法的收敛条件.理论分析表明,在智能体的非线性函数未知情况下,利用所提算法可以使非仿射非线性多智能体系统在给定时间区间上随迭代次数增加逐次实现一致性完全跟踪.最后,通过仿真算例进一步验证所提算法的有效性.     

网络环境下固定拓扑的多电机领航跟随控制

基于多智能体一致性理论,从领航跟随控制的角度解决网络环境下多电机的同步控制问题,其中考虑了网络时延对同步控制的影响。每个电机均被视为一个智能体,且每个智能体能且只能得到其邻域的输出测量信息,在此条件下,研究了在有向固定网络拓扑情况下多电机系统的同步控制问题。为了解决网络时延对电机同步控制的影响,提出了一种带有分布式观测器的时延一致性控制协议,应用 Lyapunov稳定性理论证明了若单个电机是能观能控的,只要网络连接满足简单的拓扑结构,则多电机系统能够达到领航跟随一致性。最后通过仿真实验验证了该方法的正确性和有效性。     

非线性网络有限时间分布式跟踪控制

针对具有本质非线性动态的多智能体网络,基于微分包含理论研究有限时间协调跟踪问题。假设非线性动态满足Lipschitz条件且只有部分智能体已知目标动态,设计分布式混杂控制协议,应用非光滑稳定性分析方法给出系统实现有限时间跟踪的充分条件。若无向切换拓扑保持连通或有向拓扑具有生成树且强连通部分满足细致平衡条件,则选取合适的控制增益参数均能实现有限时间跟踪。最后通过仿真实验表明了所提出方案的有效性和正确性。     

采用速度观测器的多Euler-Lagrange系统一致性跟踪控制

本文针对无向图拓扑网络下的多Euler-Lagrange系统,设计了一种分布式跟踪控制策略.在只有部分智能体能够获取领航智能体信息,且各Euler-Lagrange系统模型未知的情况下,针对领航智能体速度恒定和时变两种情况进行研究,分别设计相应观测器实现了对领航者速度的观测,且观测值的导数连续,并给出了观测器收敛的充分条件.控制器由两部分组成:第1部分是一个神经网络系统的输出,以逼近系统的未知非线性环节,第2部分是一个鲁棒项,以消除逼近误差与系统外部扰动的影响,保证控制量的连续性.采用Lyapunov理论证明了闭环系统的稳定性,通过仿真验证了本文所提算法的有效性.     

非线性多智能体系统的无模型自适应聚类一致性控制

针对一类模型未知的离散时间非线性多智能体系统聚类一致性问题,提出一种无模型自适应控制算法.首先,假设系统具有固定拓扑,利用伪偏导数概念得到系统的数据关系模型,在考虑多智能体之间耦合系数条件下给出聚类一致性误差,在此基础上设计一种数据驱动的聚类一致性跟踪控制协议;然后,采用压缩映射方法在理论上分析了跟踪误差的收敛性,结果表明所提出算法不需要智能体模型信息即可完成跟踪任务,是一种数据驱动的控制方法;最后,将结果拓展至随机切换拓扑结构的多智能体系统中,数值仿真结果验证了所提出算法的有效性.     

积分事件触发策略下的线性多智能体系统领导跟随一致性

研究有向切换拓扑下线性多智能体系统的事件触发一致跟踪问题.大多数已有的工作研究了固定拓扑下的事件触发控制,然而,当智能体间联系随时间发生改变或通信拓扑随时间发生变化时,该控制策略失效.鉴于此,在考虑切换拓扑的基础上提出一种基于积分型事件触发的控制策略.首先,当拓扑图包含一棵生成树且领导者是根节点时,利用Lyapunov稳定性理论、代数图论和矩阵变换,基于积分型事件触发控制协议,在切换拓扑下多智能体系统达到领导跟随一致性;然后,当存在多个领导者时,基于设计的触发机制在切换拓扑下多智能体系统实现包含控制,上述两种情况下闭环系统均不存在Zeno现象;最后,通过仿真结果验证控制策略的有效性.     

Exponential Consensus for Nonlinear Multi‐Agent Systems with Communication and Input Delays via Hybrid Control

This paper aims to investigate the exponential leader‐following consensus for nonlinear multi‐agent systems with time‐varying communication and input delays by using hybrid control. Based on the Lyapunov functional method, impulsive differential equation theory and matrix analysis, we show that all the followers can achieve leader‐following consensus with the virtual leader exponentially even if only a fraction of followers can obtain the leader's information. Two classes of exponential consensus criteria as well as the convergence rates for the controlled multi‐agent systems are presented under very relaxed interaction topology conditions, i.e., the directed interaction topology among the followers is only required to have p(p>1) disjoint strong components. Finally, two numerical examples are given to validate the proposed theoretical results.     

Cooperative fuzzy adaptive output feedback control for synchronisation of nonlinear multi-agent systems under directed graphs

This paper considers the leader-following synchronisation problem of nonlinear multi-agent systems with unmeasurable states and a dynamic leader whose input is not available to any follower. Each follower is governed by a nonlinear system with unknown dynamics. Two distributed fuzzy adaptive protocols, based on local and neighbourhood observers, respectively, are proposed to guarantee that the states of all followers synchronise to that of the leader, under the condition that the communication graph among the followers contains a directed spanning tree. Based on Lyapunov stability theory, the synchronisation errors are guaranteed to be cooperatively uniformly ultimately bounded. Two examples are provided to show the effectiveness of the proposed controllers.     

Cooperative Adaptive Fuzzy Output Feedback Control for Synchronization of Nonlinear Multi‐Agent Systems in the Presence of Input Saturation

This paper considers the leader‐following synchronization problem of nonlinear multi‐agent systems with unmeasurable states in the presence of input saturation. Each follower is governed by a class of strict‐feedback systems with unknown nonlinearities and the information of the leader can be accessed by only a small fraction of followers. An auxiliary system is introduced and its states are used to design the cooperative controllers for counteracting the effect of input saturation. By using fuzzy logic systems to approximate the unknown nonlinearities, local adaptive fuzzy observers are designed to estimate the unmeasurable states. Dynamic surface control (DSC) is employed to design distributed adaptive fuzzy output feedback controllers. The developed controllers guarantee that the outputs of all followers synchronize to that of the leader under directed communication graphs. Based on Lyapunov stability theory, it is proved that all signals in the closed‐loop systems are semiglobally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. An example is provided to show the effectiveness of the proposed control approach.     

基于有向网络的一致性跟踪算法

研究了leader有控制输入且followers未知该输入条件下的线性多智能 体一致性跟踪问题.提出两种一致性跟踪算法,证明两种算法在leader到followers存在一棵 有向生成树且follower间拓扑是有向条件下,网络就能跟踪leader的状态.对于第一种算法,节点根 据相邻节点或leader的状态来求解其控制输入,并基于代数Riccati不等式给出 连续情形下算法稳定性条件.第二种算法直接利用相邻节点或leader的状态,使followers在上述网络条件下跟踪leader的状态,同样基于代数Riccati不等式给出算法稳定性条件. 仿真结果验证了算法的有效性.     

Prescribed performance global stable adaptive neural dynamic surface consensus tracking control of stochastic multi-agent systems with hysteresis inputs and nonlinear dynamics

This paper focuses on the leader-following consensus control problem of stochastic multi-agent systems with hysteresis inputs and nonlinear dynamics. A leader-following consensus scheme is presented for stochastic multi-agent systems directions under directed graphs, which can achieve predefined synchronisation error bounds. By mainly activating an auxiliary robust control component for pulling back the transient escaped from the neural active region, a multi-switching robust neuro adaptive controller in the neural approximation domain, which can achieve globally uniformly ultimately bounded tracking stability of multi-agent systems recently. A specific Nussbaum-type function is introduced to solve the problem of unknown control directions. Using a dynamic surface control technique, distributed consensus controllers are developed to guarantee that the outputs of all followers synchronise with that of the leader with prescribed performance. Based on Lyapunov stability theory, it is proved that all signals in closed-loop systems are uniformly ultimately bounded and all the follower agents can keep consensus with the leader. Two simulation examples are provided to illustrate the effectiveness and advantage of the proposed control scheme.     

Robust consensus tracking of second-order nonlinear systems using relative position information by K-filter and disturbance observer based control

This work considers the problem of distributed consensus tracking control of second-order uncertain nonlinear systems under a directed communication graph which contains a spanning tree, where the leader node is the root. It is assumed that the followers receive only the relative positions from the neighbours. For the purpose of consensus tracking controller design, in each follower, a group of K-filters is introduced so that the necessity of velocity estimating is avoided. Then we can express each follower's tracking error dynamics as a second-order system with mismatched uncertainties. And hence we can design a robust consensus tracking controller for each follower by using the combination of the backstepping design and the disturbance observer based control using only relative position information. Theoretical analysis is performed to show that the DOBs' estimation errors can be made to decay to be sufficiently small very quickly before the system states escape from the feasible region. Then we show that all the followers' states track those of the leader with arbitrarily small ultimate error bounds. And simulation examples are provided to demonstrate the performance of the proposed method.     

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems (MASs) with unknown matched nonlinear functions and actuator faults. It is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired trajectory. Moreover, the leader’s input is nonzero and not available to all followers. By using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults, respectively, the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is designed. It is proved that the state of each follower can synchronize with the leader’s state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Finally, simulation results are presented for verifying the effectiveness of the proposed control method.      

带有输出约束条件的随机多智能体系统容错控制

在有向通讯拓扑图下,针对一类具有输出约束和执行器偏差增益故障的非严格反馈随机多智能体系统,提出一种自适应神经网络容错控制设计方案.采用神经网络逼近未知非线性函数,构造障碍李雅普诺夫函数处理系统的输出约束问题,以反步法和动态面技术为框架,结合Nussbaum函数设计自适应神经网络容错控制方法.基于李雅普诺夫稳定性理论,证明所有跟随者输出与领导者输出达到一致,闭环系统的所有信号依概率半全局一致最终有界且系统输出限制在给定紧集内.论文最后通过仿真实验验证所给出控制方案的有效性.     

Disturbance observer–based consensus tracking for nonlinear multiagent systems with switching topologies

This paper considers the leader‐follower consensus tracking problem for nonlinear multiagent systems with external disturbances and switching topologies. A distributed disturbance observer is constructed to estimate the disturbances suffered by the followers. Then, a distributed consensus protocol is proposed for the consensus tracking problem with disturbance rejection under a fixed directed topology based on the disturbance observer. Next, this result is extended to the case in which the switching communication topology only frequently but not always contains a directed spanning tree. By selecting the parameters appropriately such that the communication time satisfies various preset conditions, it is theoretically proven that the consensus tracking with disturbance rejection can also be achieved by the multiagent systems. Finally, a simulation example is presented to demonstrate the performance of the proposed control scheme.