摘要
应用现代时间序列分析方法,基于受控的自回归滑动平均(CARMA)新息模型,提出了随机控制系统稳态Kalman滤波器增益的两种新算法,避免了求解Riccati方程.为保证滤波器的渐近稳定性,给出了选择滤波初值的两个公式.
Using the modern time series analysis method, based on the controlled autoregressive moving average(CARMA) innovation model, two new algorithms of steady state Kalman filter gain for stochastic control systems are presented, where the solution of the Riccati equation is avoided. In order to ensure the asymptotic stability of the filter, two formulae of setting initial filtering estimate are given. A simulation example shows the effectiveness of the new algorithms.
出处
《自动化学报》
EI
CSCD
北大核心
2000年第1期74-78,共5页
Acta Automatica Sinica
基金
国家自然科学基金资助项目!( 6 9774 0 1 9)
关键词
随机控制系统
KALMAN滤波器
增益算法
Stochastic control systems, algorithms of steady state Kalman filter gain, asymptotic stability, modern time series analysis.
