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.     

基于相对位置信息的多智能体系统自适应跟踪控制

针对带有动态领导者的多智能体系统,为了使其达到跟踪一致性,设计只依赖于相对位置信息的自适应跟踪控制律.根据接收到的相对位置信息为每个跟随者设计动态输出反馈控制律,并根据控制律估计出智能体之间的相对速度信息.在此基础上设计自适应跟踪控制律,并且通过Lyapunov 稳定性理论和矩阵理论分析得到使系统达到跟踪一致性的充分条件.最后通过数值仿真验证了所提出的设计方法的有效性.     

测量受限线性多智能体系统一致性迭代学习控制

本文针对通讯拓扑同时沿时间轴和迭代轴切换且存在测量受限的情形,研究了基于迭代学习控制方法的连续线性多智能体系统输出一致性跟踪问题.在系统通信拓扑始终含有以虚拟领航者为根节点的生成树,以及所有智能体初态在每次迭代均可重置的条件下,针对跟随者能够获得的局部信息而设计了测量受限分布式输出一致性协议.然后,利用λ范数的方法和圆盘定理给出了所有跟随者的输出收敛到虚拟领导者输出的两个充分性条件,其中之一可实现时变迭代学习增益的分布式计算.最后,仿真结果验证了所得结论的有效性.     

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.     

切换拓扑下测量受限多智能体系统一致性迭代学习控制

针对通信拓扑至少含有一个沿迭代轴的联合生成树且同时沿有限时间轴和无限迭代轴切换的情况,文本研究了存在测量受限的连续线性多智能体系统输出一致性迭代学习控制问题.首先,文章采用迭代学习控制方法设计了一种基于跟随者局部信息的分布式输出一致性协议.然后,给出了系统可解输出一致性问题的两个充分性条件,其中之一可使跟随者实时获取迭代学习增益,避免了全局信息对学习增益设计的影响,且保证了算法的分布式实现.接着,利用λ范数理论和圆盘定理严格证明了所设计算法的收敛性.最后,通过实例仿真验证了所得结论的有效性.     

非仿射多智能体系统的自适应神经网络控制

针对有向拓扑图下一类控制方向未知的非仿射非线性多智能体系统的输出一致性问题,综合运用中值定理、RBF神经网络及其特性、Nussbaum增益函数方法和动态面控制技巧,提出一种分布式自适应神经网络控制协议,保证跟随者的输出能与领导者的输出同步,跟踪误差能保持在零点的小邻域内.采用新的非线性滤波器代替传统动态面控制方法(CDSC)的一阶线性滤波器,改善控制性能.通过一致性分析及仿真例子验证了所提控制方法的有效性.     

多智能体系统自适应跟踪控制

基于带有非线性动态的二阶多智能体系统,研究了在有动态领导者条件下的跟踪一致性问题。假设跟随者只能获取邻居智能体的相对状态信息,只有一部分跟随者可以获得领导者的位置和速度信息,领导者的控制输入非零且不被任何一个跟随者可知。在通信拓扑为无向连通图的条件下,为了避免全局信息的不确定性,设计了分布式自适应控制协议。将系统的一致性问题转化为误差系统的一致性问题,通过Lyapunov稳定性理论和矩阵理论分析得到了该协议使系统达到一致的充分条件。最后用仿真例子证明了设计方法的有效性。     

基于观测器的多智能体系统自适应跟踪控制

基于带有非线性动态的二阶多智能体系统,研究在有参考领导者条件下的跟踪一致性问题。假设跟随者之间的网络拓扑为有向图。针对跟随者不能得到自己的速度信息,为每个跟随者设计分布式观测器来估计自己的速度,在网络拓扑为有向图且在切换拓扑图的情况下给出基于观测器的自适应控制协议。利用Lyapunov稳定性理论和矩阵理论分析,得到使系统实现一致性的充分条件。仿真结果表明,在局部观测器和控制协议及自适应控制下,跟随者可以跟踪到领导者。     

完全分布式异构多智能体系统有限时间跟踪

针对异构二阶非线性多智能体系统有限时间跟踪问题,提出一种完全分布式一致性控制方法,消除对于误差上界与Laplacian矩阵特征值等全局信息的依赖.设计一种只包含局部信息的有限时间一致性协议,并提出自适应增益的分布式切换机制,使得各增益以分段常数的方式进行调节,简化了相邻两次切换时间区间内稳定性分析过程.通过反证法证明多智能体系统必将实现有限时间一致性,并且自适应增益保持有界.仿真结果验证了所提出的完全分布式一致性协议的有效性.     

二阶有向多智能体网络的可控包含控制

研究随机给定拓扑结构的二阶有向多智能体网络的可控包含控制问题.针对当前包含控制研究成果大多没有考虑多智能体网络领导者和跟随者的可控配置问题,结合复杂网络可控性理论和二分图最大匹配算法给出满足网络可控的领导者和跟随者集合,并为跟随者智能体设计相应的控制协议,驱使跟随者能够渐近收敛到由多个领导者构成的静态凸包中,从而实现网络的可控包含控制.仿真结果验证了理论分析的正确性.     

Stochastic Bounded Consensus Tracking of Second-Order Multi-Agent Systems with Measurement Noises and Sampled-Data

This paper investigates the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of an agent can only use the information measured at the sampling instants from its neighbors or the virtual leader with a time-varying reference state, and the measurements are corrupted by random noises. The probability limit theory, the algebra graph theory, and some other techniques are employed to derive the necessary and sufficient condition guaranteeing the mean square bounded consensus tracking. It turns out that the maximum allowable sampling period depends on not only the network topology but also the constant feedback gains. Furthermore, the effects of the sampling period on tracking performance, including the tracking speed and the static tracking error, are also analyzed. The results show that reducing the sampling period can accelerate the tracking speed and decrease the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Consensus tracking for second-order nonlinear multi-agent systems with switching topologies and a time-varying reference state

In this study, the authors consider the consensus tracking problem for second-order nonlinear multi-agent systems with switching topologies and a time-varying reference state. The dynamics of each agent consists of nonlinear inherent dynamics. In order to reach consensus tracking, a class of nonsmooth control protocols is proposed which only depends on the agent's own information and its neighbours’ information. With the aid of algebraic graph theory, matrix theory, and Lyapunov theory, some corresponding sufficient conditions guaranteeing consensus tracking under the proposed control protocols are derived. Finally, the numerical simulations are given to illustrate the effectiveness of the developed theoretical results.     

An adaptive control architecture for leader–follower multiagent systems with stochastic disturbances and sensor and actuator attacks

In this paper, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor and actuators. Specifically, for a class of linear leader–follower multiagent systems, we develop a new structure of the neighbourhood synchronisation error for the control design protocol of each follower. The proposed control algorithm addresses time-varying multiplicative sensor attacks on the leader state measurements. In addition, the framework addresses time-varying multiplicative actuator attacks on the followers that do not have a communication link with the leader and additive actuator attacks on all follower agents in the network. The proposed adaptive controller guarantees uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.     

Leader-following consensus of single-integrator multi-agent systems under noisy and delayed communication

This paper proposes a leader-following consensus control for continuous-time single-integrator multi-agent systems with multiplicative measurement noises and time-delays under directed fixed topologies. Each agent in the team receives imprecise information states corrupted by noises from its neighbours and from the leader; these noises are depending on the agents’ relative states information. Moreover, the information states received are also delayed by constant or time-varying delays. An analysis framework based on graph theory and stochastic tools is followed to derive conditions under which the tracking consensus of a constant reference is achieved in mean square. The effectiveness of the proposed algorithms is proved through some simulation examples.     

Distributed fuzzy adaptive event-triggered finite-time consensus tracking control for uncertain nonlinear multi-agent systems with asymmetric output constraint

This article investigates the consensus problem for uncertain nonlinear multi-agent systems (MASs) with asymmetric output constraint. Different from BLF-based constraint consensus tracking control, a novel approach based on nonlinear state-dependent function is proposed to solve the asymmetric output constraint, which need not convert output constraint into tracking error bound. First-order sliding mode differentiator is incorporated into each step of backstepping control design to reduce computation burden. Further, in combination of proposed event-triggered mechanism based on time-varying threshold, a distributed fuzzy adaptive event-triggered finite-time consensus method is developed. It can ensure that the consensus tracking error tends to a small neighbor in a finite time and the asymmetric output constraint of each subsystem is not violated. Two simulations are given to demonstrate the effectiveness of control method.     

A solution for the cooperative formation-tracking problem in a network of completely unknown nonlinear dynamic systems without relative position information

In this paper, a solution of the formation-tracking problem is provided for a network that contains nonlinear agents with completely unknown dynamics and working under unknown disturbances. By the combination of a cooperative observer and an adaptive model-free controller, the requirement of inter-agent relative position information in the network is eliminated. Here, a cooperative observer is designed to estimate the time-varying reference trajectory and the time-varying parameters of the desired formation topology at each agent in the network. The stability of the proposed cooperative observer is analysed using Lyapunov analysis. Utilising the cooperative observer, the formation-tracking problem in the network of dynamic agents is transformed to a tracking problem in a single agent system. Moreover, an adaptive model-free control policy is applied to each agent for providing the tracking objective. Utilising the algebraic connectivity originating from graph theory, this model-free control algorithm is formulated to scale-up for a network of multi-agents. The proposed decentralised controller includes two model-free adaptive laws for online estimating of the completely unknown dynamics at each agent in the network. The application of the proposed solution is simulated for a network of four quadrotors with unknown internal dynamics and unknown external disturbances.     

Stochastic bounded consensus tracking of second-order multi-agent systems with measurement noises based on sampled-data with small sampling delay

This paper is devoted to the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of each agent can only use the information measured at the sampling instants from its neighbors or the virtual leader with a time-varying reference state, the measurements are corrupted by random noises, and the signal sampling process induces the small sampling delay. The augmented matrix method, the probability limit theory and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking. We show that the convergence of the proposed protocol simultaneously depends on the constant feedback gains, the network topology, the sampled period and the sampling delay, and that the static consensus tracking error depends on not only the above mentioned factors, but also the noise intensity and the upper bound of the velocity and the acceleration of the virtual leader. The obtained results cover no sampling delay as its one special case. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

具有随机多跳时变时延的多航天器协同编队姿态一致性

针对存在随机多跳时变时延的多航天器协同编队的姿态一致性问题,本文设计了可消除随机多跳时变时延影响并能够实现多航天器协同编队姿态角速度一致及姿态角有效跟踪的静态控制器.首先基于有向图论推导出领航者一跟随者误差系统的动态方程,然后通过构造合适的Lyapunov函数将误差系统调节器问题转化为了线性矩阵不等式解的存在性问题,其次通过求解线性矩阵不等式完成了协同编队姿态控制系统的静态控制器设计.理论分析表明,所设计的控制器能够有效消除随机多跳时变时延影响,实现了多航天器协同编队的姿态一致性.数值仿真验证了所提方法的正确性和有效性.     

脉冲式事件触发控制的时变多个体系统一致性

针对时变拓扑连接环境下的时变多个体系统的一致性问题,提出基于事件触发的脉冲控制协议。在该协议里对于每个个体,只有当相关状态误差超过阈值时才会更新控制器,同时控制输入将仅在事件触发时刻执行,且个体间不需要持续通信。该协议将大幅节约系统实现一致性的通信和控制成本。使用代数图论、李雅普诺夫稳定性和脉冲微分方程等数学理论分析和推导具有时变特性的多个体系统在事件触发脉冲控制下达到一致性的充分条件,同时理论证明事件触发的时间序列不存在芝诺行为。最后,数值仿真验证了所得到的理论结论的有效性。