Work

Adaptive Experiment Design for Nonlinear System Identification With Operational Constraints

Year: 2025

Type: article

Abstract: We consider the joint problem of online experiment design and parameter estimation for identifying nonlinear system models, while adhering to system constraints. We utilize a receding horizon approach and propose a new adaptive input design criterion, which is tailored to continuously updated parameter estimates, along with a new sequential estimator. We demonstrate the ability of the method to design informative experiments online, while steering the system within operational constraints.

Source: IEEE Signal Processing Letters

DOI: 10.1109/lsp.2025.3639512

Authors: Jingwei Hu, Dave Zachariah, Torbjörn Wigren, Petre Stoica

Institution: Uppsala University

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: Vetenskapsrådet

Awards: Robust learning methods for out-of-distribution tasks, Trustworthy Bandit Algorithms for Precision Medicine