Hybrid Simulation Safety: Limbos and Zero Crossings

TL;DR

This paper addresses the challenges of ensuring simulation safety in hybrid models by focusing on zero-crossing detection and event handling, with implementations in Modelica and Ptolemy II.

Contribution

It introduces methods for safe zero-crossing detection and deterministic event handling in hybrid simulations, enhancing accuracy and reliability.

Findings

Improved zero-crossing detection techniques implemented in Modelica.

Deterministic hybrid event handling methods demonstrated in Ptolemy II.

Discussion of simulation safety issues in hybrid modeling environments.

Abstract

Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can often efficiently generate simulation traces, but how do we know that the simulation results are correct? If we detect an error, is the error in the model or in the simulation itself? This paper discusses the problem of simulation safety, with the focus on hybrid modeling and simulation. In particular, two key aspects are studied: safe zero-crossing detection and deterministic hybrid event handling. The problems and solutions are discussed and partially implemented in Modelica and Ptolemy II.