collaborators

8 papers

math.OC2026

Nonlinear Network Identifiability with Full Excitations

Renato Vizuete, Julien M. Hendrickx

We derive conditions for the identifiability of nonlinear networks characterized by additive dynamics at the level of the edges when all the nodes are excited. In contrast to linea…

eess.SY2026

Preserving Topology Privacy of Network Systems by Feedback: Conditions and Distributed Design

Yushan Li, Jiabao He, Julien M. Hendrickx +1

This paper develops a feedback-based method to preserve the topology privacy of consensus protocols in network systems. The key idea is to intentionally violate topology identifiab…

math.OC2026

Data Poisoning Attacks Can Systematically Destabilize Data-Driven Control Synthesis

Vijayanand Digge, Martina Vanelli, Ahmad W. Al-Dabbagh +2

Data-driven control has emerged as a powerful paradigm for synthesizing controllers directly from data, bypassing explicit model identification. However, this reliance on data intr…

eess.SY2025

Interpolation Conditions for Data Consistency and Prediction in Noisy Linear Systems

Martina Vanelli, Nima Monshizadeh, Julien M. Hendrickx

We develop an interpolation-based framework for noisy linear systems with unknown system matrix with bounded norm (implying bounded growth or non-increasing energy), and bounded pr…

math.OC2025

Path-Based Conditions for the Identifiability of Non-additive Nonlinear Networks with Full Measurements

Renato Vizuete, Julien M. Hendrickx

We analyze the identifiability of nonlinear networks with non necessarily additive node dynamics, where the influence of in-neighbors is represented by a multivariate nonlinear fun…

math.OC2025

Several Performance Bounds on Decentralized Online Optimization are Highly Conservative and Potentially Misleading

Erwan Meunier, Julien M. Hendrickx

We analyze Decentralized Online Optimization algorithms using the Performance Estimation Problem approach which allows, to automatically compute exact worst-case performance of opt…