网络攻击下多智能体系统数据驱动安全控制

Data-driven Security Control of Multi-agent Systems Under Cyber Attacks

研究了受到虚假数据注入攻击的单输入单输出非线性多智能体系统的分布式无模型自适应控制问题。考虑多智能体受到虚假数据注入攻击的影响,基于单智能体的紧格式动态线性化技术,提出了一种新的分布式无模型自适应控制算法。所设计的控制器不需要网络拓扑结构的信息,仅使用系统的输入输出数据,使该算法更适用于实际系统。此外,为了减少网络通信资源的占用,设计了事件触发机制,进而设计了一种基于事件触发的分布式无模型自适应安全控制算法来实现趋同控制目标。最后,使用仿真算例并通过比较来验证所提方法的有效性。

The distributed model-free adaptive control for single-input single-output nonlinear multi-agent systems under false-data-injection attack is studied.With consideration of multi-agent systems under false-datainjection attack,a novel distributed model-free adaptive control algorithm is proposed based on the compact form dynamic linearization technique for the single agent.The controller designed in this paper does not require the information of the network topology and only uses the input and output data of the system,which makes the algorithm suitable for the actual system.In addition,an event-triggered mechanism is introduced to reduce the occupation of network communication resources.Further,a flexible event-triggered distributed model-free adaptive secure control algorithm is designed to achieve the consensus control goal.Finally,simulation examples are used to verify the effectiveness of the proposed method by some comparisons.