Distributed Safe Learning using an Invariance-based Safety Framework

TL;DR

This paper introduces a safety framework for uncertain distributed linear systems that guarantees constraint satisfaction during learning by using robust invariance and backup control, suitable for resource-limited systems.

Contribution

It proposes a novel invariance-based safety framework with offline computed invariant sets and backup controllers for distributed systems with uncertainties.

Findings

Guarantees safety during learning in uncertain distributed systems.

Enables real-time safety enforcement with simple online computations.

Validated through three numerical examples.

Abstract

In large-scale networks of uncertain dynamical systems, where communication is limited and there is a strong interaction among subsystems, learning local models and control policies offers great potential for designing high-performance controllers. At the same time, the lack of safety guarantees, here considered in the form of constraint satisfaction, prevents the use of data-driven techniques to safety-critical distributed systems. This paper presents a safety framework that guarantees constraint satisfaction for uncertain distributed systems while learning. The framework considers linear systems with coupling in the dynamics and subject to bounded parametric uncertainty, and makes use of robust invariance to guarantee safety. In particular, a robust non-convex invariant set, given by the union of multiple ellipsoidal invariant sets, and a nonlinear backup control law, given by the combination of multiple stabilizing linear feedbacks, are computed offline. In presence of unsafe inputs, the safety framework applies the backup control law, preventing the system to violate the constraints. As the robust invariant set and the backup stabilizing controller are computed offline, the online operations reduce to simple function evaluations, which enables the use of the proposed framework on systems with limited computational resources. The capabilities of the safety framework are illustrated by three numerical examples.