论文标题
不确定性下的部分扩展可观察性认证和移动视野估计器的最佳设计
Partial Extended Observability Certification and Optimal Design of Moving Horizon Estimators Under Uncertainties
论文作者
论文摘要
本文介绍了在存在嘈杂的测量和参数不确定性的情况下观察参数的可观察性分析和最佳设计。主要的基础框架是通过随机优化的非线性约束移动范围估计器设计和概率认证。由于在考虑的不确定和嘈杂的环境下，完美的可观察性概念无关紧要，因此引入了几乎$ε$ - 观察性的概念，并且可以绘制出具有先验已知的测量噪声统计数据和参数差异的系统过程，以评估其对给定系统的满意度。提出的框架中的一个不错的功能是，可观察性不一定定义为重建整个状态的能力，而是使用观察目标数量的更一般的概念，以便可以分析可以重建状态和参数的特定表达式的精度。通过一个说明性示例公开并验证了整个框架。
This paper addresses the observability analysis and the optimal design of observation parameters in the presence of noisy measurements and parametric uncertainties. The main underlying frameworks are the nonlinear constrained moving horizon estimator design and the probabilistic certification via randomized optimization. As the perfect observability concept is not relevant under the considered uncertain and noisy context, the notion of almost $ε$-observability is introduced and a systematic procedure to assess its satisfaction for a given system with a priori known measurement noise statistics and parameter discrepancy is sketched. A nice feature in the proposed framework is that the observability is not necessarily defined as the ability to reconstruct the whole state, rather, the more general concept of observation-target quantities is used so that one can analyze the precision with which specific chosen expressions of the state and the parameters can be reconstructed. The overall framework is exposed and validated through an illustrative example.
