A Particle Filter Approach to Robust State Estimation for a Class of Nonlinear Systems with Stochastic Parameter Uncertainty
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概要
- 論文の詳細を見る
In this paper, we propose a robust state estimation method using a particle filter (PF) for a class of nonlinear systems which have stochastic parameter uncertainties. A robust PF was designed using prediction and correction structure. The proposed PF draws particles from a simple proposal density function and corrects the particles with particle-wise correction gains. We present a method to obtain an error variance of each particle and its upper bound, which is minimized to determine the correction gain. The proposed method is less restrictive on system nonlinearities and noise statistics; moreover, it can be applied regardless of system stability. The effectiveness of the proposed robust PF is illustrated via an example based on Chuas circuit.
- （社）電子情報通信学会の論文
- 2011-05-01
著者
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Won Sangchul
Department Of Electrical Engineering Pohang University Of Science And Technology
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Won Sangchul
Department Of Electronic And Electrical Engineering Postech
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KIM Sehoon
Department of Electronic and Electrical Engineering, POSTECH
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Kim Sehoon
Department Of Electronic And Electrical Engineering Postech
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