1.东南大学数学学院,江苏南京 211189
2.东南大学自动化学院,江苏南京 210096
[ "李晓东 男,1995年6月出生于山东省泰安市。现为东南大学数学学院数学专业博士研究生。主要研究方向为多智能体系统、攻击检测与分布式控制。E-mail: 230208654@seu.edu.cn" ]
[ "温广辉 1983年10月出生于河南省平顶山市。现为东南大学自动化学院首席教授、博士生导师。主要研究方向为智能系统、复杂网络化系统、分布式控制与优化、弹性控制与强化学习。E-mail: ghwen@seu.edu.cn" ]
收稿:2026-01-20,
录用:2026-02-24,
纸质出版:2026-02-25
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李晓东, 温广辉. 执行器攻击下开放式异构多智能体系统的自适应输出一致性[J]. 电子学报, 2026, 54(02): 698-709.
LI Xiaodong, WEN Guanghui. Adaptive Output Consensus of Heterogeneous Open Multi-Agent Systems under Actuator Attacks[J]. Acta Electronica Sinica, 2026, 54(02): 698-709.
李晓东, 温广辉. 执行器攻击下开放式异构多智能体系统的自适应输出一致性[J]. 电子学报, 2026, 54(02): 698-709. DOI:10.12263/DZXB.20251224
LI Xiaodong, WEN Guanghui. Adaptive Output Consensus of Heterogeneous Open Multi-Agent Systems under Actuator Attacks[J]. Acta Electronica Sinica, 2026, 54(02): 698-709. DOI:10.12263/DZXB.20251224
本文研究了受到执行器攻击的开放式异构多智能体系统的自适应输出一致性问题。在复杂的工业互联网与现代集群系统应用场景中,多智能体系统常因任务编组调整、通信链路波动、节点故障与动态接入等因素而呈现出显著的开放式特性,具体表现为系统节点集合与整体维数随时间演化,通信拓扑呈现时变、间歇性连通与重构切换等复杂特性,从而使群体动力学结构与可获得信息结构具有更强的时变性与不确定性。与此同时,分布式控制信号通常需要经由网络化通道传输并在执行器端接收并执行,一旦攻击者在执行器侧进行恶意数据注入,控制输入将被叠加未知干扰甚至被篡改为具有误导性的指令,从而导致智能体实际执行行为偏离预期并破坏协同一致性,显著增加分布式控制设计与一致性分析的难度。针对上述挑战,本文首先利用智能体的输出信息构造了一种具有攻击免疫能力的降阶观测器,在不对执行器攻击进行显式估计的前提下获取控制所需的局部状态信息,降低了估计成本。在此基础上,本文进一步设计了一种完全分布式的自适应弹性控制协议,该协议仅利用相邻智能体之间的交互信息及本地观测量即可在线调节耦合增益与攻击补偿参数,实现对攻击影响的抑制以及对拓扑不确定性的自适应处理。该方法不需要任何全局拓扑信息与攻击上界信息,因此能够适应开放式网络环境下的节点数量动态变化以及拓扑切换等情形,具有良好的可扩展性与工程可实现性。为刻画开放式异构多智能体系统的结构特性与误差演化机理,本文建立了一种用于描述系统跟踪误差演化的统一分析框架,并在该框架下推导了执行器攻击存在时实现输出一致性的平均驻留时间条件,从而给出拓扑切换频率与系统收敛性能之间的关系。最后,通过数值仿真对所提出方法进行验证,并与现有算法进行对比。结果表明在相同攻击条件与网络环境下,本文方法能够有效抑制攻击对群体行为的影响并提升收敛速度,从而验证了所提出降阶观测器与完全分布式自适应弹性控制策略的有效性与优势。
This paper investigates the adaptive output consensus problem of heterogeneous open multi-agent systems under actuator attacks. In complex application scenarios such as the industrial internet and modern cluster systems
multi-agent systems often exhibit open characteristics due to task reconfiguration
fluctuations in communication links
node faults
and dynamic joining/leaving. Specifically
the node set and the overall system dimension may evolve over time
and the communication topology may exhibit time-varying behavior
intermittent connectivity
and reconstruction-induced switching. These characteristics make both the collective dynamics and the available information structure strongly time-varying and uncertain. Meanwhile
distributed control signals typically need to be transmitted through networked channels and received and executed at the actuator. Once an attacker injects malicious data into the actuators
the control inputs can be superimposed with unknown disturbances or even tampered into misleading commands
causing the agents’ actual behaviors to deviate from their intended actions and thereby destroying cooperative consensus. These issues significantly increase the difficulty of distributed controller design and consensus analysis. To address these challenges
an attack-free reduced-order observer is designed based solely on output information. Without explicitly estimating actuator attacks
the proposed observer provides the local state information required for control design
thereby reducing the estimation cost. Building upon this
a fully distributed adaptive resilient control protocol is developed. The protocol relies solely on local observations and interaction information exchanged among neighboring agents to adjust the coupling gains and attack-compensation parameters online
achieving both suppression of attack effects and adaptive handling of topology uncertainties. Notably
the proposed method requires neither any global topology information nor prior knowledge of attack bounds. Thus
it is well suited to open network environments with dynamically changing numbers of nodes and topology switching
offering excellent scalability and practical implementability. To characterize the structural properties and error propagation mechanism of heterogeneous open multi-agent systems
a unified analytical framework is established to describe the evolution of the tracking error. Based on this framework
an average dwell-time condition is derived to guarantee output consensus of the system under actuator attacks
thereby revealing the relationship between the topology switching rate and the system’s convergence performance. A numerical simulation is provided to demonstrate the effectiveness of the proposed approach and to compare it with existing algorithms. The results show that
under the same attack conditions and network settings
the proposed method effectively mitigates the impact of attacks on collective behaviors and improves the convergence speed
thereby demonstrating the effectiveness and advantages of the proposed reduced-order observer and fully distributed adaptive resilient control strategy.
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