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A proximity moving horizon estimator for a class of nonlinear systems
International Journal of Adaptive Control and Signal Processing ( IF 3.1 ) Pub Date : 2020-01-28 , DOI: 10.1002/acs.3092
Meriem Gharbi 1 , Christian Ebenbauer 1
Affiliation  

In this article, we present a proximity‐based formulation for moving horizon estimation (MHE) of a class of constrained discrete‐time nonlinear systems. The cost function of the proposed estimator includes a convex stage cost as well as a Bregman distance for the a priori estimate. This rather general formulation of the cost function allows for a flexible design of the estimator depending on the setting of the problem at hand. We derive sufficient conditions for the global exponential stability of the underlying estimation error. We also investigate the robustness properties of the proposed MHE scheme applied for linear systems subject to unknown process and measurement disturbances in terms of an input‐to‐state stability analysis. The estimator performance is illustrated by means of simulation examples.

中文翻译:

一类非线性系统的接近运动视界估计器

在本文中,我们为一类受约束的离散时间非线性系统的移动视界估计(MHE)提供了一种基于邻近度的公式。所提出的估计器的成本函数包括凸阶段成本以及先验估计的布雷格曼距离。成本函数的这种相当笼统的表述允许根据手头问题的设置灵活地设计估算器。我们为基础估计误差的全局指数稳定性得出了充分的条件。我们还从输入到状态稳定性分析的角度,研究了拟议的MHE方案的鲁棒性,该方案适用于受到未知过程和测量干扰的线性系统。估计器性能通过仿真示例进行说明。
更新日期:2020-01-28
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