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A UD factorization-based nonlinear adaptive set-membership filter for ellipsoidal estimation

机译:基于UD分解的椭圆估计非线性自适应集员滤波器。

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摘要

The extended set-membership filter (ESMF) for nonlinear ellipsoidal estimation suffers from numerical instability. computation complexity as well as the difficulty in filter parameter selection. In this paper, a UD factorization-based adaptive set-membership filter is developed and applied to nonlinear joint estimation of both time-varying stales and parameters. As a result of using the proposed UD factorization, combined with a new sequential and selective measurement update strategy, the numerical stability and real-time applicability of conventional ESMF are substantially improved. Furthermore, an adaptive selection scheme of the filter parameters is derived to reduce the computation complexity and achieve sub-optimal estimation. Simulation results have shown the efficiency and robustness of the proposed method. Copyright (C) 2007 John Wiley & Sons, Ltd.
机译:用于非线性椭球估计的扩展集成员资格滤波器(ESMF)遭受数值不稳定的困扰。计算复杂度以及滤波器参数选择的难度。本文研究了一种基于UD分解的自适应集合成员滤波器,并将其应用于时变模型和参数的非线性联合估计。使用建议的UD分解的结果,结合新的顺序和选择性测量更新策略,大大提高了常规ESMF的数值稳定性和实时适用性。此外,推导了滤波器参数的自适应选择方案,以降低计算复杂度并实现次优估计。仿真结果表明了该方法的有效性和鲁棒性。版权所有(C)2007 John Wiley&Sons,Ltd.

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