The algorithmic analysis of hybrid systems

TLDR

A hybrid system consists of a discrete program with an analog environment. We present a general framework for the formal specification and algorithmic analysis of hybrid systems. The authors model hybrid systems as finite automata with continuous variables governed by dynamical laws, restrict to linear hybrid systems with piecewise‑linear trajectories, and employ symbolic model‑checking and minimization that iteratively compute state sets as unions of convex polyhedra, providing approximation techniques when convergence fails. They establish decidability and undecidability results for classes of linear hybrid systems and demonstrate that standard program‑analysis techniques can be adapted to these systems.

Abstract

We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as finite automata equipped with variables that evolve continuously with time according to dynamical laws. For verification purposes, we restrict ourselves to linear hybrid systems, where all variables follow piecewise-linear trajectories. We provide decidability and undecidability results for classes of linear hybrid systems, and we show that standard program-analysis techniques can be adapted to linear hybrid systems. In particular, we consider symbolic model-checking and minimization procedures that are based on the reachability analysis of an infinite state space. The procedures iteratively compute state sets that are definable as unions of convex polyhedra in multidimensional real space. We also present approximation techniques for dealing with systems for which the iterative procedures do not converge.