带有完全分布式观测器的多智能体系统自适应容错一致性

针对一类同时带有执行器故障,未知非线性动态和非匹配干扰的多智能体系统,本文提出一种新的自适应容错控制方案.首先,设计一种适用于有向切换拓扑的完全分布式观测器估计领导者的信息,将一致性问题转化为局部的信号跟踪问题.其次,拆解转化后的误差系统为两个耦合的子系统,实现非匹配干扰与匹配因子分离.然后,利用径向基神经网络近似非线...     

Distributed containment control with multiple stationary or dynamic leaders in fixed and switching directed networks

In this paper, we study the problem of distributed containment control of a group of mobile autonomous agents with multiple stationary or dynamic leaders under both fixed and switching directed network topologies. First, when the leaders are stationary and all followers share an inertial coordinate frame, we present necessary and sufficient conditions on the fixed or switching directed network topology such that all followers will ultimately converge to the stationary convex hull formed by the stationary leaders for arbitrary initial states in a space of any finite dimension. When the directed network topology is fixed, we partition the (nonsymmetric) Laplacian matrix and explore its properties to derive the convergence results. When the directed network topology is switching, the commonly adopted decoupling technique based on the Kronecker product in a high-dimensional space can no longer be applied and we hence present an important coordinate transformation technique to derive the convergence results. The proposed coordinate transformation technique also has potential applications in other high-dimensional distributed control scenarios and might be used to simplify the analysis of a high-dimensional system to that of a one-dimensional system when the decoupling technique based on the Kronecker product cannot be applied. Second, when the leaders are dynamic and all followers share an inertial coordinate frame, we propose a distributed tracking control algorithm without velocity measurements. When the directed network topology is fixed, we derive conditions on the network topology and the control gain to guarantee that all followers will ultimately converge to the dynamic convex hull formed by the dynamic leaders for arbitrary initial states in a space of any finite dimension. When the directed network topology is switching, we derive conditions on the network topology and the control gain such that all followers will ultimately converge to the minimal hyperrectangle that contains the dynamic leaders and each of its hyperplanes is normal to one axis of the inertial coordinate frame in any high-dimensional space. We also show via some counterexamples that it is, in general, impossible to find distribute containment control algorithms without velocity measurements to guarantee that all followers will ultimately converge to the convex hull formed by the dynamic leaders under a switching network topology in a high-dimensional space. Simulation results are presented as a proof of concept.     

Fault‐tolerant containment control of uncertain nonlinear systems in strict‐feedback form

This paper investigates the containment control problem of uncertain nonlinear strict‐feedback systems in the presence of actuator faults. The communication topology among the agents is directed, and there exists at least one leader that has a directed path to each follower. Based on fuzzy logic systems and the dynamic surface control technique, a fault‐tolerant containment control scheme is developed to guarantee that the outputs of all followers converge to the convex hull spanned by multiple dynamic leaders with bounded containment errors. The result is extended to a fault‐tolerant containment control with prescribed performance, such that the error surfaces are confined to predefined bounds regardless of actuator faults. Simulation results are provided to illustrate the effectiveness of the proposed methods. Copyright © 2016 John Wiley & Sons, Ltd.     

Distributed finite‐time containment control for multiple Euler‐Lagrange systems with communication delays

In this paper, distributed finite‐time containment control for multiple Euler‐Lagrange systems with communication delays and general disturbances is investigated under directed topology by using sliding‐mode control technique. We consider that the information of dynamic leaders can be obtained by only a portion of the followers. Firstly, a nonsingular fast terminal sliding surface is selected to achieve the finite‐time convergence for the error variables. Then, a distributed finite‐time containment control algorithm is proposed where the neural network is utilized to approximate the model uncertainties and external disturbances of the systems. Furthermore, considering that error constraint method can improve the performance of the systems, a distributed finite‐time containment control algorithm is developed by transforming the error variable into another form. It is demonstrated that the containment errors are bounded in finite time by using Lyapunov theory, graph theory, and finite‐time stability theory. Numerical simulations are provided to show the effectiveness of the proposed methods.     

Distributed containment control for nonlinear multiagent systems in pure‐feedback form

In this paper, the problem of distributed containment control for pure‐feedback nonlinear multiagent systems under a directed graph topology is investigated. The dynamics of each agent are molded by high‐order nonaffine pure‐feedback form. Neural networks are employed to identify unknown nonlinear functions, and dynamic surface control technique is used to avoid the problem of explosion of complexity inherent in backstepping design procedure. The Frobenius norm of the ideal neural network weighting matrices is estimated, which is helpful to reduce the number of the adaptive tuning law and alleviate the networked communication burden. The proposed distributed containment controllers guarantee that all signals in the closed‐loop systems are cooperatively semiglobally uniformly ultimately bounded, and the outputs of followers are driven into a convex hull spanned by the multiple dynamic leaders. Finally, the effectiveness of the developed method is demonstrated by simulation examples.     

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.     

优化目标可变的容错三维拓扑控制算法

为了使无线网络满足连通性、节能、干扰较小和容错等要求,采用对节点发送功率进行适当调整的拓扑控制技术是一种十分有效的方法。现实中的Ad Hoc网络应用场景的通信情况复杂多变,网络的优化目标也可能随之发生改变。提出一种更加贴近真实环境的容错三维拓扑控制算法-OVFSS,在拓扑容错的前提下,该算法在干扰对网络影响较大时能将干扰优化到最小,在干扰影响较小时能较好地考虑节能。     

Containment control for second-order nonlinear multi-agent systems with intermittent communications

This article investigates the containment control problem for a class of second-order multi-agent systems with inherent nonlinear dynamics, under the common assumption that each agent can only obtain the relative information of its neighbours intermittently. A kind of distributed protocol based only on the relative local intermittent measurements of neighbouring agents is designed for containment control under fixed directed topology. In the absence of delays, based on the Lyapunov function technology and the intermittent control method, some sufficient conditions are presented to guarantee the intermittent containment control of second-order nonlinear multi-agent systems. In the presence of delays, some containment conditions are also obtained for a second-order multi-agent systems with inherent delayed nonlinear dynamics and intermittent communications. Moreover, the similar results are obtained for second-order nonlinear multi-agent systems under switching directed topology. Finally, simulation examples are given to illustrate the correctness and effectiveness of the theoretical analysis.     

Distributed finite‐time fault‐tolerant error constraint containment algorithm for multiple ocean bottom flying nodes with tan‐type barrier Lyapunov function

The ocean bottom flying node (OBFN) is a special autonomous underwater vehicle (AUV) for seabed resource exploration. In this article, unmodeled uncertainties, thruster faults, and ocean disturbances are considered. The trajectory errors are constrained. Based on the directed topology, the distributed finite‐time fault‐tolerant error constraint containment control problem for multiple OBFN systems is solved, while only a part of follower OBFNs can measure the state of leaders. By using the backstepping method and a tan‐type barrier lyapunov function (BLF), a novel form of virtual controller is constructed. Neural network is employed to approximate and compensate the general disturbances. And the upper bound of the estimation error is dealt with by proposing an adaptive law. Besides, the trajectory errors can be constrained to a small neighborhood of zero in finite time. In other words, follower OBFNs can reach the convex hull consisted of leaders in finite time. The effectiveness of the designed algorithm is shown by presenting numerical experiment.     

无需相对速度信息的多Euler-Lagrange 系统自适应神经网络包含控制

对含有模型非线性不确定性和外部扰动的多Euler-Lagrange 系统的分布式协调包含控制问题进行研究. 考虑通讯拓扑为有向图, 所有领航者均为动态, 且各智能体间相对速度信息不可测情况. 首先, 选取相对速度作为辅助变量, 引入低通滤波器进行估计; 然后, 采用神经网络方法逼近并补偿非线性不确定性, 提出一种分布式自适应包含控制律, 并应用Lyapunov 稳定性理论证明闭环系统的包含误差一致最终有界; 最后, 通过仿真算例验证了所提出的控制律的有效性.

     

基于BP神经网络的矿井提升机自校正容错PID控制

针对矿井提升机系统故障时动态性能难以用传统的解析方法获得的问题,提出了一种基于BP神经网络的矿井提升机自校正容错PID控制方法。该方法通过BP神经网络在线学习跟踪提升机系统的动态特性来预测系统输出值,并应用自适应控制中的自校正PID构建容错控制器,实现提升机系统故障下的稳定容错控制。仿真结果表明,该方法在提升机系统故障情况下能迅速跟踪系统故障状态,在线调整PID参数,快速恢复系统性能。     

A low‐complexity design for distributed containment control of networked pure‐feedback systems and its application to fault‐tolerant control

This paper addresses a low‐complexity distributed containment control problem and its extension to fault‐tolerant control for networked nonlinear pure‐feedback systems under a directed graph. The multiple dynamic leaders are neighbors of only a subset of the followers described by completely non‐affine multi‐input multi‐output pure‐feedback dynamics. It is assumed that all followers' nonlinearities are heterogeneous and unknown. The proposed containment controller is implemented by using only error surfaces integrated by performance bounding functions and does not require any differential equations for compensating uncertainties and faults. Thus, compared with the previous containment control approaches for multi‐agent systems with unknown non‐affine nonlinearities, the distributed containment control structure is simplified. In addition, it is shown that the proposed control scheme can be applied to the fault‐tolerant containment control problem in the presence of unexpected system and actuator faults, without reconstructing any control structure. It is shown from Lyapunov stability theorem that all followers nearly converge to the dynamic convex hull spanned by the dynamic leaders and the containment control errors are preserved within certain given predefined bounds. Copyright © 2016 John Wiley & Sons, Ltd.     

Command-filter-based distributed containment control of nonlinear multi-agent systems with actuator failures

In this paper, the problem of distributed containment fault-tolerant control for a class of nonlinear multi-agent systems in strict-feedback form is studied. The considered nonlinear multi-agent systems are subject to unknown nonlinear functions and actuator faults with loss of effectiveness and lock-in-place. By resorting to the universal approximation capability of fuzzy logical systems, the command filtered backstepping technique and nonlinear fault-tolerant control theory, distributed controllers are designed recursively. From the Lyapunov stability theory, it is proved that all signals of the resulting closed-loop systems are cooperatively semi-globally uniformly ultimately bounded and the containment errors converge to a small neighbourhood of origin by properly tuning the design parameters. Finally, a numerical example is provided to show the effectiveness of the proposed control method.     

Semi‐global and global containment control of multi‐agent systems with second‐order dynamics and input saturation

This paper considers both semi‐global and global containment control for a second‐order multi‐agent system that is composed by a network of identical harmonic oscillators or double integrators with multiple leaders and input saturation. A distributed low gain feedback algorithm is proposed to solve the semi‐global containment control problem for the network whose topology is directed and initial condition is taken from any a priori given bounded set. In particular, by using a parametric Lyapunov equation approach, M‐matrix properties and algebraic graph theory, an upper bound of the low gain parameter is estimated such that the low gain feedback matrix can be analytically determined without involving numerical computation. Furthermore, under the assumption that the induced subgraph formed by the followers is strongly connected and detail balanced, two linear feedback protocols are designed for coupled harmonic oscillators and coupled double integrators, respectively, to asymptotically achieve the global containment control of the network with any initial condition. Finally, numerical examples are given to illustrate the effectiveness of the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

Event-based broadcasting containment control for multi-agent systems under directed topology

The event-based broadcasting containment control problem for both first-order and second-order multi-agent systems under directed topology is investigated. Based on certain event, each agent decides when to transmit its current states to its neighbours and the agents’ distributed control algorithms are based on these sampled state measurements, which can significantly decrease the number of the controllers’ updates. All the agents are divided into two groups, namely, the leaders and the followers. The formation control is introduced. The leaders exchange their information to converge to a formation. The followers utilise the information from both their leader neighbours and their follower neighbours and are driven to the convex hull of the leaders using the proposed control algorithms. Numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results.     

VTFTR：高维胖树中的无死锁容错路由算法

随着近年来高性能计算系统规模的急剧扩大,高性能互连网络的可靠性成为愈发重要的问题。高维胖树是一种结合了胖树与多维环网优点的网络拓扑结构,凭借其良好的可扩展性与网络性能在E级时代具有广阔的应用前景。然而,目前关于高维胖树中容错路由算法的相关研究较为有限,其可靠性问题亟待解决。为提高高维胖树拓扑在高性能互连网络中的容错能力,进一步提高对应超算系统的运行效率,提出一种用于高维胖树中叶交换机故障的容错路由算法VTFTR。该算法结合转向模型与虚通道切换的思想,通过严格控制报文在无故障路径与容错路径中的转向,使用少量的容错虚通道与额外跳步实现高维胖树中的无死锁容错。实验结果表明,在单点故障情况下,VTFTR算法的容错路径较对比算法有2~4个跳步的减少,在4 096个节点规模的网络中,当叶交换机故障数量为10时,在故障叶交换机不同的分布情况下,该算法能够以1.4%~2.0%的吞吐率下降作为代价来保持全网无故障节点之间的互连。     

无线传感执行器网络中多源容错拓扑控制算法研究

拓扑控制是延长无线传感器网络生命时间的关键技术.针对异构网络的复杂性,提出了基于功率控制的分布式多源容错拓扑控制算法MSFT.在由大量计算、能量受限的传感器节点和少量性能较优的执行器节点组成的异构无线传感执行器网络模型中,算法保证任意传感器节点与执行器节点之间至少存在k条不相交路径同时选择权值较优节点使路径总功耗尽可能少,这样当任意k-1个节点失效时并不影响网络的连通性.理论分析证明算法能以O(n)的时间和消息代价构造网络拓扑,仿真实验进一步证实算法的有效性.