# Robust Contraction Analysis of Nonlinear Systems via Differential IQC

arXiv: https://arxiv.org/abs/1903.08806 · HTML: https://mlsanity.com/paper/1903.08806/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2019.

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

- [Scalable Incremental Robustness Analysis of Neural Network Feedback Systems](https://mlsanity.com/paper/2609.22576/) (2026)

## Abstract (arXiv)

We present a new approach to verifying contraction and L2-gain of uncertain nonlinear systems, extending the well-known method of integral quadratic constraints. The uncertain system consists of a feedback interconnection of a nonlinear nominal system and uncertainties satisfying differential integral quadratic constraints. A pointwise linear matrix inequality condition is formulated to verify the closed-loop differential  L2  gain, which can lead to global reference-independent  L2  gain performance of the nonlinear uncertain system. For a polynomial nominal system, the convex verification conditions can be solved via sum-of-squares programming. A simple computational example based on jet-engine surge with input delays illustrates the approach.