确保估计性能的离散Markov跳跃系统鲁棒Kalman滤波

Robust Kalman filtering of discrete-time Markov ian jump systems based on state estimation performance

本文研究一类具有不确定噪声的离散时间Markov跳跃线性系统的鲁棒Kalman滤波器设计问题.文中基于确保状态估计误差性能指标的原理,给出了不确定噪声协方差矩阵的扰动上界,并在此界限内采用最坏情况下的最优滤波器实现对状态的估计.该设计方案不仅能极小化不确定下的最坏性能,而且能够确保性能指标达到给定的某个自由度.文中给出数值算例表明了设计方案的有效性.

Robust Kalman filtering problems for a class of discrete-time Markovian jump systems with unknown bounded noises are investigated in this paper. The upper bound of the disturbance of the noise covariance matrix is given based on the estimation error performance, and an optimal state estimation is therefore adopted under the worst condition. Not only can this method minimize the worst performance function of the uncertainty, but the error performance can also be guaranteed to be within the given range of precision. A numerical example shows the validity of the method.