Scholarlink

<p>This brief communication aims to present a topic about iterative data assimilation in the set-based filtering context. Recent state estimators based on constrained zonotopes, such as CZMV (mean value extension), CZFO (first-order extension) and CZDC (DC programming), assimilate data simultaneously, that is, fixing some sets over the consistency steps. This process may deteriorate the precision of sets because the approximation remainder depends on the state forecast, which is being fixed to execute the conventional way of generalized intersection. Therefore, using the CZDC as basis, we propose its iterative version. In order to reduce computational effort, we also propose an iterative interval filter. These algorithms are tested in a 2D case study with both nonlinear process and measurement equations to illustrate the expected improvement of precision and/or performance over CZDC.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Set-Based State Estimators with Iterative Update

  • 期刊论文

  • 发表日期：

    2026年2月18日

查看全文
  • Alesi A. de Paula,
  • Áureo d. S. Santos,
  • William J. de Lima

摘要

This brief communication aims to present a topic about iterative data assimilation in the set-based filtering context. Recent state estimators based on constrained zonotopes, such as CZMV (mean value extension), CZFO (first-order extension) and CZDC (DC programming), assimilate data simultaneously, that is, fixing some sets over the consistency steps. This process may deteriorate the precision of sets because the approximation remainder depends on the state forecast, which is being fixed to execute the conventional way of generalized intersection. Therefore, using the CZDC as basis, we propose its iterative version. In order to reduce computational effort, we also propose an iterative interval filter. These algorithms are tested in a 2D case study with both nonlinear process and measurement equations to illustrate the expected improvement of precision and/or performance over CZDC.