# Adaptive Experiment Design for Nonlinear System Identification with Operational Constraints

arXiv: https://arxiv.org/abs/2502.20941 · HTML: https://mlsanity.com/paper/2502.20941/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2025.

## Built on by (most cited first, 1 of 1)

- [Information-theoretic receding-horizon active learning of nonlinear dynamical systems](https://mlsanity.com/paper/2609.36712/) (2026)

## Abstract (arXiv)

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.