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On the application of a hybrid ellipsoidal-rectangular interval arithmetic algorithm to interval Kalman filtering for state estimation of uncertain systems

机译:椭球-矩形混合区间算法在区间卡尔曼滤波不确定系统状态估计中的应用

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摘要

© 2015 Taylor and Francis. Modelling uncertainty is a key limitation to the applicability of the classical Kalman filter for state estimation of dynamic systems. For such systems with bounded modelling uncertainty, the interval Kalman filter (IKF) is a direct extension of the former to interval systems. However, its usage is not yet widespread owing to the over-conservatism of interval arithmetic bounds. In this paper, the IKF equations are adapted to use an ellipsoidal arithmetic that, in some cases, provides tighter bounds than direct, rectangular interval arithmetic. In order for the IKF to be useful, it must be able to provide reasonable enclosures under all circumstances. To this end, a hybrid ellipsoidal-rectangular enclosure algorithm is proposed, and its robustness is evidenced by its application to two characteristically different systems for which it provides stable estimate bounds, whereas the rectangular and ellipsoidal approaches fail to accomplish this in either one or the other case.
机译:©2015泰勒和弗朗西斯。建模不确定性是经典卡尔曼滤波器对动态系统状态估计的适用性的关键限制。对于具有有限建模不确定性的此类系统,间隔卡尔曼滤波器(IKF)是前者到间隔系统的直接扩展。但是,由于间隔算术界限的过度保守性,其用法尚未普及。在本文中,IKF方程适用于使用椭圆算法,在某些情况下,椭圆算法提供的边界比直接矩形区间算法更严格。为了使IKF有用,它必须能够在所有情况下提供合理的外壳。为此,提出了一种混合椭球-矩形包围算法,其鲁棒性通过将其应用到两个特性不同的系统中来证明,该系统为其提供了稳定的估计范围,而矩形和椭球方法则无法在其中一个或一个中完成该任务。其他情况。

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