多不确定系统的Krein空间鲁棒滤波方法

Jin Feng, Fei Yu, Na Yang, Pengyu Zhang, Wei Gao, Xin Zhang
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引用次数: 2

摘要

本文提出了一种新的多不确定性线性系统鲁棒滤波的Krein空间方法。多重不确定性满足能量型约束,同时进入状态方程和测量方程。该方法用于解决由系统不确定性和二次约束(SQC)引起的子优化问题。为此,设计了一种新颖的Krein空间形式系统。然后从形式系统中导出递归估计。并给出了估计达到最优的充分必要条件。最后,通过数值算例验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Krein space approach to robust filtering for multiple uncertain systems
In this paper, a new Krein space approach to robust filtering for linear systems with multiple uncertainties is developed. The multiple uncertainties satisfy the energy-type constraints, entering into both state and measurement equations. The proposed approach is used to tackle the sub-optimization problem arising from a sum quadratic constraint (SQC) of system uncertainties. To this end, a novel Krein space formal system is designed. Then recursive estimation is derived from the formal system. Also, the necessary and sufficient condition for the estimation to be optimal is proposed. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.
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