# Regional stability conditions for recurrent neural network-based control systems

arXiv: https://arxiv.org/abs/2409.15792 · HTML: https://mlsanity.com/paper/2409.15792/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2024.

## Built on by (most cited first, 3 of 3)

- [Controller Design for Structured State-space Models via Contraction Theory](https://mlsanity.com/paper/2604.07069/) (2026)
- [Recurrent neural network-based robust control systems with regional properties and application to MPC design](https://mlsanity.com/paper/2506.20334/) (2025)
- [LoRA-RC: Reservoir Computing with Low-Rank Adaptation](https://mlsanity.com/paper/2609.12327/) (2026)

## Abstract (arXiv)

In this paper we propose novel global and regional stability analysis conditions based on linear matrix inequalities for a general class of recurrent neural networks. These conditions can be also used for state-feedback control design and a suitable optimization problem enforcing H2 norm minimization properties is defined. The theoretical results are corroborated by numerical simulations, showing the advantages and limitations of the methods presented herein.