Robust guaranteed cost observer design for linear uncertain jump systems with state delays

This paper deals with the robust guaranteed cost observer with guaranteed cost performance for a class of linear uncertain jump systems with state delay.The transition of the jumping parameters in systems is governed by a finite-state Markov process.Based on the stability theory in stochastic differential equations,a sufficient condition on the existence of the proposed robust guaranteed cost observer is derived.Robust guaranteed cost observers are designed in terms of a set of linear coupled matrix inequalities.A convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost observers.

有失序量测的随机卡尔曼滤波状态更新最优解

在中心式多传感器跟踪系统中,经常会出现同一目标的量测没有按照正常的时间顺序到达处理中心的现象.如何利用(相对当前最新时刻而言)负时点的失序量测本更新状态的问题在现实的多传感器系统中普遍存在.对于具有确定性参数矩阵的卡尔曼滤波,Bar-Shalom于2002年给出了利用失序量测的最优状态更新估计方程.本文作者将此结果进一步推广到了具有随机参数矩阵的卡尔曼滤波,给出了利用失序量测时当前状态的最优更新估计方程.

不确定多通道信号鲁棒稳态估计

对于一类具有随机参数矩阵、不确定噪声方差、一步随机时滞、丢包和丢失观测的多通道自回归(Autoregressive,AR)信号系统,文章研究其鲁棒稳态Kalman滤波问题.应用状态空间方法,增广方法和虚拟噪声技术,混合不确定AR信号模型被转换为仅带不确定噪声方差和相同过程以及观测噪声的状态空间模型.根据极大极小鲁棒估计原理,基于带不确定噪声方差保守上界的最坏情形系统,提出了鲁棒稳态Kalman一步和多步信号预报器.证明了所提出的信号预报器的鲁棒性,即对于所有容许的不确定性,信号预报器的实际稳态预报误差方差被保证有相应的最小上界.仿真例子验证了所提出方法的正确性和有效性.