基于间歇测量的状态估计稳定性和精度研究*

针对分布式控制系统状态估计过程出现的测量值丢失问题,本文量化分析测量值丢失对估计稳定性和精度的影响。首先,根据随机测量模型重新推导带测量值丢失的卡尔曼滤波器,得到估计误差协方差迭代式。然后,将随机误差协方差迭代式建模为修正的黎卡提微分方程,提出了估计稳定性和精度分析方法。最后,列举不同的系统实例,证明临界包到达率的存在性,当测量值到达率大于临界值时,平均误差协方差从发散过渡到有界,进而得到估计精度与包达率之间的函数关系。

Stability and Accuracy Analysis of State Estimation Over Intermittent Measurements

This paper quantitatively analyzes the influence of the loss of measured values on the stability and accuracy of the estimation for the loss of measured values in the state estimation process of distributed control systems. Firstly, a Kalman filter with measurement loss is deduced from the stochastic measurement model, and a estimation error covariance iterative. Then, the random error covariance iteration is modeled as a modified Riccati differential equation, and the Kalman filter estimation stability theory is proposed. Finally, the paper gives some different system examples to show the existence of the critical arrival rate of the distributed control system, when the arrival rate of the measured value is greater than the critical value, the mean error covariance transits from divergence to boundedness, And obtains the function relationship between the state estimation accuracy and the packet arrival rate.