Robust Kalman Filtering for the Discrete-Time Interval System
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摘要: 着重研究区间系统的鲁棒滤波问题.通过等价变换,将区间系统转换为对应的矩阵 范数不确定系统,并据此导出区间系统的鲁棒滤波算法.该算法为一离散验后(a posteriori) 滤波算法,它能保证区间系统的滤波误差有界.理论分析和实际计算结果表明,本算法能达到 比验前(a priori)滤波小得多的滤波误差的方差上界.Abstract: This paper deals with the robust Kalman filtering method for the discrete-time interval system. By equivalent transformation, the interval system is transformed to an uncertain system with matrix norm bounds. Then a posteriori robust Kalman filter is proposed, which can guarantee a variance bound of the filtering error. Both analysis and practical computing show that this filter can get a much lower variance bound than a priori one can.
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Key words:
- Robust filtering /
- interval system /
- robust identification /
- state estimation
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