欺骗攻击下具备隐私保护的多智能体系统均值趋同控制

针对通信网络遭受欺骗攻击的离散时间多智能体系统,研究其均值趋同和隐私保护问题.首先,考虑链路信道存在窃听者的情形,提出一种基于状态分解思想的分布式网络节点值重构方法,以阻止系统初始信息的泄露.其次,针对所构建的欺骗攻击模型,利用重构后节点状态信息并结合现有的安全接受广播算法,提出一种适用于无向通信网络的多智能体系统均值趋同控制方法.理论分析表明,该方法能够有效保护节点初始状态信息的隐私,并能消除链路中欺骗攻击的影响,实现分布式系统中所有节点以初始值均值趋同.最后,通过数值仿真实验验证了该方法的有效性.     

DoS攻击下多智能体系统无模型自适应迭代学习跟踪控制EI北大核心CSCD

针对周期性拒绝服务(DoS)攻击下多智能体系统有限时间趋同跟踪控制问题,本文提出了一种无模型自适应迭代学习控制(MFAILC)算法.假设多智能体系统具有固定拓扑结构,并且仅有部分智能体可获取到期望轨迹信息.在多智能体系统数据传输过程中,需要经由对数量化器进行量化处理.首先,使用伪偏导数将智能体系统动态线性化,处理过程中考虑符合伯努利分布的周期性DoS攻击现象,在此基础上设计了MFAILC控制算法,其次,采用压缩映射方法给出了一个在期望意义下保证跟踪误差收敛的充分条件,并在理论上证明了所提算法的收敛性.所提算法只需利用系统的输入输出数据就可完成趋同跟踪任务.最后,仿真结果验证了所提算法的有效性.     

DoS攻击下电力网络控制系统脆弱性分析及防御

考虑DoS攻击对电力信息物理系统的影响,提出一种电力网络控制系统脆弱节点的检测方法和防御策略,采用分布式控制架构设计传感器和RTU的传输路径.通过求解最稀疏矩阵优化问题,提出一种识别并保护电力通信网脆弱节点和边的方法,保证系统实现安全稳定运行.进一步提出一种可以抵御DoS攻击的电力网络控制系统拓扑设计方法,研究系统遭受DoS攻击时能恢复稳定的电力网络控制系统拓扑连接方式. IEEE 9节点系统用于仿真验证,充分验证了算法的可行性和可靠性,并针对该9节点电力网络控制系统,给出了具体的网络攻击防御策略.     

输出饱和多智能体系统的迭代学习趋同跟踪控制

针对带有输出饱和的多智能体系统有限时间趋同跟踪控制问题,提出了一种分布式迭代学习控制算法.首先假设多智能体系统具有固定拓扑结构,且仅有部分智能体可获取到期望轨迹信息.基于输出约束条件构造一致性跟踪误差,在此基础上设计了P型迭代学习控制率.然后采用压缩映射方法给出了一个算法收敛的充分条件,并在理论上证明了跟踪误差的收敛性.最后,将理论结果推广至具有随机切换拓扑结构的多智能体系统中.仿真结果验证了所提出算法的有效性.     

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...     

DoS攻击下基于多率采样的多智能体系统安全一致性

本 文 研 究 了 一 类 带 有 多 率 采 样 的 线 性 多 智 能 体 系 统(Multiagent Systems, MASs)在 拒 绝 服 务(Denial-of-Service, DoS)攻击下的安全一致性控制问题, 其中DoS攻击通常阻断智能体之间的信息传输. 本文将多 率采样在网络化控制系统中的结果推广到了多智能体系统, 并考虑了非理想通信网络环境. 首先, 通过引入一个匹 配机制来同步由多率采样引起的智能体不同状态分量的采样数据. 然后, 在DoS攻击下, 针对带有多率采样的线 性MAS提出了一个基于多率采样的安全一致性控制器. 通过使用李雅普诺夫稳定性理论和切换系统方法, 获得了 包含DoS 攻击持续时间以及攻击频率的安全一致性充分条件. 最后, 给出了一个仿真例子来验证所提方法的有效 性, 并给出了多率采样与单率采样机制的性能对比分析.     

基于免疫的对等网络DoS攻击防御系统

通过学习自然免疫系统和研究对等网络DoS问题与传统网络中的区别,提出了一种基于免疫的对等网络DoS攻击防御系统。在系统中,对等网每个节点都有一个可根据环境学习和动态改变的免疫智能体,它能够自动检测网络并对具有DoS攻击特征的数据进行控制,从而把攻击扼杀在萌芽状态。系统具有分布性、自适应性、可扩展性等特点。     

拒绝服务攻击下领导-跟随多智能体系统的均方一致性研究

针对带有过程噪声和测量噪声的领导-跟随多智能体系统,研究拒绝服务攻击下多智能体系统的一致性问题.首先,设计基于卡尔曼滤波的状态观测器,对智能体状态进行有效准确的估计;然后,基于预测控制理论提出一种基于状态估计信息的分布式预测控制算法,从而实现领导-跟随多智能体系统的均方一致性控制,并给出拒绝服务攻击环境下实现领导-跟随多智能体系统均方一致性的充分必要条件;最后,通过数值仿真验证所提出方法的正确性和有效性.     

列车控制系统的抗拒绝服务攻击弹性控制策略

当遭受拒绝服务(DoS)攻击时,分布式列车控制系统的弹性控制问题受到广泛关注.本文提出了一种基于分布式领导车状态观测器和障碍李雅普诺夫函数的弹性控制策略,不仅可以避免列车碰撞,同时实现了编队控制的目标.首先,给出了一种分布式的领导车状态观测器设计方法,用于实时估计领导车的状态.理论分析表明,在DoS攻击满足一定约束的条件下,该状态观测器的估计误差具有指数稳定特性.在此基础上,通过将列车碰撞避免问题转化为状态受限问题,提出一种基于障碍李雅普诺夫函数的状态受限控制律,解决了DoS攻击下确保碰撞避免的车队控制问题.最后,数值仿真证实了本文方法的有效性.     

DoS攻击下一类二阶多智能体系统的安全分组一致性研究

针对拒绝服务(denial-of-service, DoS)攻击下一类二阶多智能体系统的安全分组一致性协同控制问题,区别于同类工作,在非周期性多信道独立的攻击场景下,基于复杂系统中智能体间的合作与竞争交互,提出一种新的带有状态估计器的安全分组一致性控制协议.在该协议的作用下,首先,给出DoS攻击持续时间的约束条件,通过设计合适的李雅普诺夫函数,结合求解代数黎卡提方程得到不同攻击模式下信道的衰减率;然后,通过引入与各个信道对应的等效衰减率,克服所得衰减率与信道难以匹配的问题,并给出系统的稳定性判据;最后,通过数值实验验证理论分析所得结论的正确性和有效性.     

Dynamic-estimator-based adaptive secure containment control for constrained nonlinear multi-agent systems under denial-of-service attacks

This article concentrates upon the adaptive secure containment control problem for a class of uncertain nonlinear multi-agent systems with the output constraint requirements under denial-of-service (DoS) attacks. At first, to overcome the difficulty that the tracking performance of the nonlinear multi-agent systems under the DoS attacks is disturbed seriously, a novel adaptive secure containment control approach is presented by applying a DoS attacks detection mechanism and introducing the barrier Lyapunov functions, which enables the system to achieve the security control objective that the output of each agent eventually converges to the convex hull spanned by the dynamic leaders' outputs, while never violating the output constraints. Then, a state estimator is designed, which reconstructs the immeasurable states of the multi-agent systems and approximates the completely unknown nonlinearities arising from the agents. In addition, the dynamic surface control technique is used to solve the “explosion of complexity” problem. It is demonstrated that the proposed anti-attack controller ensures that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the theoretical results.     

面向网络攻击下弹性均值趋同的智能体群组编队

本文研究通信范围有限的智能体群组编队问题,探索网络攻击下多智能体系统弹性均值趋同控制策略.现有的工作表明,多智能体系统可通过维持一个所谓r–鲁棒的通信网络,实现分布式弹性趋同控制器的设计.然而,传统的方法中只有当单个智能体的通信范围足够大时,才能使网络满足r–鲁棒这一特定条件.本文利用智能体可移动的特性放宽了对通信范围...     

Interval consensus problem of multi-agent systems in accordance with switching protocol

In this paper, we discuss the interval consensus problem of multi-agent systems by providing a special Laplacian of directed graphs. As one of the most important issues in the coordination control of multi-agent systems, the consensus problem requires that the output of several spatially distributed agents reach a common value that depends on the states of all agents. For the given consensus protocol and initial states, a fixed consensus value is obtained. The resulting consensus value, however, may not be ideal or meet the quality that we require from the multi-agent system. In this paper, by introducing two state-dependent switching parameters into the consensus protocol, the system given by the proposed protocol can globally asymptotically converge to a designated point on a special closed and bounded interval. In other words, the system given by the proposed protocol can globally asymptotically reach interval consensus and then the system can also achieve a generalised interval average consensus if the directed graph is balanced. Simulations are presented to demonstrate the effectiveness of our theoretical results.     

Encryption–decryption-based event-triggered consensus control for nonlinear MASs under DoS attacks

In this article, the consensus tracking problem is discussed for a class of discrete-time nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks. The individual agents interact with each other via communication network whose topology is assumed to be time-varying and strongly connected. Two techniques are employed to deal with the network-induced complexities. On one hand, an event-triggering scheme is adopted to regulate the data transmission among agents with the purpose of making full utilization of the limited communication resources; and on the other hand, an encryption–decryption mechanism is designed with the aim to provide compensation, thereby mitigating the DoS attack effects. It is the objective of the addressed problem to develop a distributed model-free adaptive control law to enforce the MASs achieve desirable consensus performance. By using a specific projection algorithm in combination with a dynamic linearization method, the desired control protocol is formulated explicitly, whose effectiveness and applicability are demonstrated via an illustrative numerical example.     

An overview on multi-agent consensus under adversarial attacks

This paper presents an overview on the recent advances in the research of security of cyber–physical systems. We place particular emphases on consensus problems for multi-agent systems in hostile environments and their analyses on the resiliency against two types of attacks. First, we discuss a class of data injection attacks by focusing on the approach based on mean subsequence reduced (MSR) algorithms and their variants. Agents equipped with such algorithms will ignore their neighbors taking extreme state values. Characterizations on the properties necessary for network topologies and moreover a number of extensions with enhanced resiliency will be established. As the second class of attacks, the effects of denial-of-service (DoS) attacks will be examined in the context of multi-agent consensus. By employing a DoS model based on the energy constraints of the attacker, we will observe that robustness against such attacks may depend on system properties such as dynamics of the individual agents and network structures. Applications of the algorithms will be further discussed for clock synchronization in wireless sensor networks and control of a group of mobile robots.     

Solving a modified consensus problem of linear multi-agent systems

A distributed protocol is proposed for a modified consensus problem of a network of agents that have the same continuous-time linear dynamics. Each agent estimates its own state using its output information and then sends the estimated state to its neighbor agents for the purpose of reaching a consensus. The modified consensus problem requires the group decision value to be a linear function of initial states and initial estimated states of all agents in the network, and the transformation matrix associated with this linear function not to be a zero matrix. It is proved that under the proposed control protocol, the modified consensus problem can be solved if and only if the system matrices of the agent’s dynamics are stabilizable and detectable, the input matrix is not a zero matrix, and the communication topology graph has a spanning tree. The proposed protocol can also be extended to multi-agent systems where agents are described by discrete-time linear dynamics. The corresponding necessary and sufficient conditions are provided as well.     

Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks

This paper investigates the event-triggered security consensus problem for nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks over an undirected graph. A novel adaptive memory observer-based anti-disturbance control scheme is presented to improve the observer accuracy by adding a buffer for the system output measurements. Meanwhile, this control scheme can also provide more reasonable control signals when DoS attacks occur. To save network resources, an adaptive memory event-triggered mechanism (AMETM) is also proposed and Zeno behavior is excluded. It is worth mentioning that the AMETM’s updates do not require global information. Then, the observer and controller gains are obtained by using the linear matrix inequality (LMI) technique. Finally, simulation examples show the effectiveness of the proposed control scheme.      

高阶离散多智能体系统在参数不确定和带外部干扰下的鲁棒H∞一致性控制

研究了高阶离散多智能体系统的在参数不确定和带外部干扰下的H_∞鲁棒一致性控制问题,同时提出线性分布式一致性协议.首先将该问题转化为一组不确定系统的H_∞鲁棒控制问题.其次推导出线性矩阵不等式在参数为γ的H_∞鲁棒一致性意义下的充分条件.第三,给出了所提出一致性协议在不带外部干扰,参数不确定的高阶离散线性多智能体系统中的收敛效果.最后,通过包含和不包含参数不确定系统的对比仿真实验说明了理论结果的正确性和有效性.