针对复杂协同攻击下一类非线性系统的状态估计问题，提出一种分布式一致性递推滤波算法。首先，将拒绝服务攻击(denial of service，DoS)和虚假数据注入攻击(false data injection，FDI)现象描述为两个随机Bernoulli序列，并利用统一的框架建立包含DoS和FDI的复杂协同攻击模型;然后，基于一致性理论设计具有分布式结构的递推滤波器，计算最优滤波器增益，并推导该滤波器估计误差满足均方有界的充分必要条件;最后，利用室内机器人的定位问题进行验证，仿真结果验证了所提出滤波器算法的有效性。
Distributed consensus filter design for a class of nonlinear systems under complex cooperative attacks
Aiming at the state estimation problem of a class of nonlinear systems under complex cooperative attack,a distributed consensus-based recursive filtering algorithm is proposed.Firstly,the phenomena of denial of service(DoS)and false data injection(FDI)are described as two random Bernoulli sequences,and a complex cooperative attack model including DoS and FDI is established by using a unified framework.Then,a recursive filter with distributed structure is designed based on the consensus theory,the optimal filter gain is calculated,and the necessary and sufficient conditions for the estimation error of the filter to meet the mean square boundedness are derived.Finally,the indoor robot positioning problem is used to verify the effectiveness of the proposed filter algorithm
NETL
NSTL
万方数据
维普
