非线性系统最小成本空间填充实验设计
系统与控制
2026-05-13 v2 系统与控制
摘要
非线性模型估计的质量高度依赖于用于系统识别的数据质量。通过采用基于高斯过程的优化输入设计方法，可生成特征空间中的空间填充数据集。该设计方法适用于广泛的信号和模型类型，并通过最优准则纳入信息度量。然而， resulting input design can be costly to apply to the real system. The goal of this paper is to propose a space-filling input design that can minimize the experimentation cost in terms of a user defined measure, while still guaranteeing a prescribed level of space-fillingness. Through a Monte Carlo simulation study we demonstrate that the proposed method can appropriately shape the excitation signal to significantly reduce the experimental cost while the identified model performance remains adequate.
引用
@article{arxiv.2605.02517,
title = {Least Costly Space-Filling Experiment Design for the Identification of a Nonlinear System},
author = {Máté Kiss and Maarten Schoukens and Roland Tóth},
journal= {arXiv preprint arXiv:2605.02517},
year = {2026}
}