Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems With the Denial-of-Service Attacks and Stochastic Communication Protocol

In this paper, a new filtering fusion problem is studied for nonlinear cyber-physical systems under error-variance constraints and denial-of-service attacks. To prevent data collision and reduce communication cost, the stochastic communication protocol is adopted in the sensor-to-filter channels to regulate the transmission order of sensors. Each sensor is allowed to enter the network according to the transmission priority decided by a set of independent and identically-distributed random variables. From the defenders’ view, the occurrence of the denial-of-service attack is governed by the randomly Bernoulli-distributed sequence. At the local filtering stage, a set of variance-constrained local filters are designed where the upper bounds (on the filtering error covariances) are first acquired and later minimized by appropriately designing filter parameters. At the fusion stage, all local estimates and error covariances are combined to develop a variance-constrained fusion estimator under the federated fusion rule. Furthermore, the performance of the fusion estimator is examined by studying the boundedness of the fused error covariance. A simulation example is finally presented to demonstrate the effectiveness of the proposed fusion estimator.      

不完全量测的误差方差约束下的容许采样频率

本文主要研究了不完全量测的误差方差约束下的传感器所能容许的采样频率这一问题. 分析了不完全量测下的目标跟踪系统的误差方差的稳态特性, 给出了不完全量测下误差协方差阵的一些性质. 在给定探测概率下, 利用线性矩阵不等式(LMI)求解这一问题. 工程意义在于, 在满足给定滤波器的误差方差约束指标下, 可以选择采样间隔较长的传感器, 放宽对传感器的采样频率的要求, 从而降低测量装置成本. 数值算例说明了算法的有效性.     

Variance-constrained filtering for discrete-time genetic regulatory networks with state delay and random measurement delay

This paper is concerned with the variance-constrained filtering problem for a class of discrete-time genetic regulatory networks (GRNs) with state delay and random one-step measurement delay. The phenomenon of the random one-step measurement delay is characterised by a random variable, which is assumed to obey the Bernoulli distribution with known occurrence probability. The purpose of the addressed problem is to design a filter such that, in the presence of state delay and random one-step measurement delay, an upper bound of the filtering error covariance matrix can be obtained and the explicit expression of the filter gain matrix is given. Then, the proposed variance-constrained filtering method can be used to approximate the concentrations of mRNAs and proteins. Finally, a numerical example is provided to illustrate the effectiveness of the designed filtering scheme.     

离散随机系统的容错约束方差控制设计

本文考虑线性离散随机系统的容错约束方差控制设计问题，即设计反馈控制器，使闭环系统在可能的传感器失效不仅保持渐近稳定，而且满足预先给定的稳态方差约束，文中导出期望了容约束方差控制器存在的充分条件，并进一步给出了其参数化代数表达式。     

不完全量测下目标跟踪系统的容许量测噪声

针对目标跟踪系统不可避免存在的量测值丢失的情况,研究了统计意义下基于不完全量测的估计误差协方差的性质,并分析了稳态滤波误差方差与量测噪声之间的关系。当传感器探测概率已知,在给定的误差方差约束下,给出了考虑不完全量测条件下滤波器的一种新算法,可使系统具有最大容许量测噪声强度,从而可降低对传感器精度的要求。数值算例和蒙特卡罗(Monto Carlo)仿真结果表明了该方法的有效性。