HYSDEL—A Tool for Generating Computational Hybrid Models for Analysis and Synthesis Problems

TLDR

The authors develop HYSDEL, a high‑level modeling language and computational framework for discrete‑time hybrid systems that enables translation between hybrid model paradigms. They define a class of discrete hybrid automata (DHA), relate it to existing paradigms such as piecewise affine, mixed logical dynamical, linear complementarity, and min‑max‑plus‑scaling systems, and provide tools to translate DHA into these models. HYSDEL’s multimodeling capability allows practitioners to apply a wide range of analysis and synthesis techniques, as demonstrated by an automotive example that showcases the use of multiple computational tools across different model representations.

Abstract

This paper presents a computational framework for modeling hybrid systems in discrete-time. We introduce the class of discrete hybrid automata (DHA) and show its relation with several other existing model paradigms: piecewise affine systems, mixed logical dynamical systems, (extended) linear complementarity systems, min-max-plus-scaling systems. We present HYSDEL (hybrid systems description language), a high-level modeling language for DHA, and a set of tools for translating DHA into any of the former hybrid models. Such a multimodeling capability of HYSDEL is particularly appealing for exploiting a large number of available analysis and synthesis techniques, each one developed for a particular class of hybrid models. An automotive example shows the modeling capabilities of HYSDEL and how the different models allow to use several computational tools.