# Optimal input design for non-linear dynamic systems: a graph theory approach

arXiv: https://arxiv.org/abs/1310.4706 · HTML: https://mlsanity.com/paper/1310.4706/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Oct 2013.

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

- [Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model](https://mlsanity.com/paper/2504.05490/) (2025)

## Abstract (arXiv)

In this article a new algorithm for the design of stationary input sequences for system identification is presented. The stationary input signal is generated by optimizing an approximation of a scalar function of the information matrix, based on stationary input sequences generated from prime cycles, which describe the set of finite Markov chains of a given order. This method can be used for solving input design problems for nonlinear systems. In particular it can handle amplitude constraints on the input. Numerical examples show that the new algorithm is computationally attractive and that is consistent with previously reported results.