Compositional Analysis of Hybrid Systems Defined Over Finite Alphabets

TL;DR

This paper develops a scalable, dissipativity-based compositional analysis method for large-scale hybrid systems combining continuous and finite-alphabet discrete dynamics, enabling stability and input-output analysis.

Contribution

It introduces a scalable, distributed approach using accelerated ADMM for analyzing large hybrid systems with semi-definite programming.

Findings

Method effectively analyzes systems with 60 continuous and 18 discrete states.

Semi-definite programs can be solved efficiently for smaller systems.

Distributed computation enhances scalability for large hybrid systems.

Abstract

We consider the stability and the input-output analysis problems of a class of large-scale hybrid systems composed of continuous dynamics coupled with discrete dynamics defined over finite alphabets, e.g., deterministic finite state machines (DFSMs). This class of hybrid systems can be used to model physical systems controlled by software. For such classes of systems, we use a method based on dissipativity theory for compositional analysis that allows us to study stability, passivity and input-output norms. We show that the certificates of the method based on dissipativity theory can be computed by solving a set of semi-definite programs. Nonetheless, the formulation based on semi-definite programs become computationally intractable for relatively large number of discrete and continuous states. We demonstrate that, for systems with large number of states consisting of an interconnection of smaller hybrid systems, accelerated alternating method of multipliers can be used to carry out the computations in a scalable and distributed manner. The proposed methodology is illustrated by an example of a system with 60 continuous states and 18 discrete states.