摘要
应用时域上的现代时间序列分析方法 ,基于 ARMA新息模型和白噪声估计理论 ,由一种新的非递推最优状态估值器的递推变形 ,提出了广义系统 Wiener状态滤波的一种新算法 ,它可统一处理滤波、平滑和预报问题 ,且具有渐近稳定性。同某些算法相比 ,它避免了求解 Riccati方程和 Diophantine方程 ,且避免了计算伪逆 ,因而减小了计算负担。
A new algorithm to Wiener state filtering for descriptor systems is presented by using the modern time-series analysis method in the time domain. The algorithm is based on the autoregressive moving average (ARMA) innovation model and white noise estimation theory, and exploits a recursive version of a new non-recursive optimal state estimators. It can handle the filtering, smoothing and prediction problems in a unified framework, and has the asymptotic stability. Compared with some existing algorithms, it avoids solving the Riccati equations and Diophantine equations, and avoids the calculation of the pseudo-inverse, which reduces the computational burden. A simulation example shows its effectiveness.
出处
《控制与决策》
EI
CSCD
北大核心
2003年第3期328-331,共4页
Control and Decision
基金
国家自然科学基金资助项目 ( 697740 19)
黑龙江省自然科学基金资助项目 ( F0 1- 15 )
