Distributed Stability Certification and Control from Local Data
Surya Malladi, Nima Monshizadeh

TL;DR
This paper develops distributed algorithms enabling multiple agents with limited local data to collaboratively compute global system stability certificates and controllers without sharing raw data.
Contribution
It introduces novel distributed methods for Lyapunov and Riccati equation solutions, allowing decentralized stability certification and control design.
Findings
Distributed Lyapunov certification achieved for LTI systems.
Distributed LQR controller design demonstrated for helicopter dynamics.
Algorithms show robustness to noise and data limitations.
Abstract
Most data-driven analysis and control methods rely on centralized access to system measurements. In contrast, we consider a setting in which the measurements are distributed across multiple agents and raw data are not shared. Each agent has access only to locally held samples, possibly as little as a single measurement, and agents exchange only locally computed signals. Consequently, no individual agent possesses sufficient information to identify the entire system or synthesize a controller independently. To address this limitation, we develop distributed dynamical algorithms that enable the agents to collectively compute global system certificates from local data. Two problems are addressed. First, for stable linear time-invariant (LTI) systems, the agents compute a Lyapunov certificate by solving the Lyapunov equation in a fully distributed manner. Second, for general LTI systems,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Control Systems Optimization · Model Reduction and Neural Networks · Distributed Control Multi-Agent Systems
