基于反攻击控制策略的多智能体系统安全集隶属度形成。

IF 6.5 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Zehui Xiao , Jie Tao , Wei Meng , Peng Shi
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引用次数: 0

摘要

研究了受参数扰动和饱和约束的多智能体系统的安全先导-跟随形成问题。为了捕捉攻击行为在不同阶段的变化,利用具有时变转移概率的马尔可夫过程建立了一个更通用的DoS攻击模型。在此基础上,提出了一种基于内存的防攻击方案来设计基于安全观测器的控制器,为削弱DoS攻击对编队控制的影响提供了一种有效的方法。在此基础上,引入集隶属度概念,推导出一步超前编队误差始终局限于跟踪椭球集的充分条件。结合充分条件和饱和约束,提出了求解最优椭球集的优化问题。为了达到leader-follow编队,提出了一种在线优化算法递归求解基于观测器的控制器。为了降低优化问题的执行频率,在优化算法中嵌入了一种具有攻击相关自适应阈值的事件触发机制。最后,通过仿真实例验证了所提方法的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure set-membership formation of multi-agent systems via an anti-attack control strategy
Secure leader-following formation for multi-agent systems subject to parameter perturbations and saturation constraints is investigated in this article. To capture the variation of attack behaviors across different stages, a more general DoS attack model is developed using a Markov process with time-varying transition probabilities. Then, a memory-based anti-attack scheme is presented for designing the secure observer-based controller, supplying an effective method to weaken the impact of DoS attacks on formation control. Subsequently, the set-membership concept is introduced to derive some sufficient conditions such that the one-step ahead formation errors are always confined to the tracking ellipsoidal set. Combining the sufficient conditions with saturation constraints, an optimization problem is proposed to obtain the optimal ellipsoidal sets. For reaching the leader-following formation, an online optimization algorithm is provided to recursively solve the observer-based controller. To reduce the execution frequency of the optimization problem, a novel event-triggered mechanism with attack-dependent adaptive threshold is embedded in the optimization algorithm. Finally, the effectiveness and advantages of the proposed methods are certified via a simulation example.
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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