Article ID Journal Published Year Pages File Type
430733 Journal of Computer and System Sciences 2012 34 Pages PDF
Abstract

Hybrid system modelers have become a corner stone of complex embedded system development. Embedded systems include not only control components and software, but also physical devices. In this area, Simulink is a de facto standard design framework, and Modelica a new player. However, such tools raise several issues related to the lack of reproducibility of simulations (sensitivity to simulation parameters and to the choice of a simulation engine). In this paper we propose using techniques from non-standard analysis to define a semantic domain for hybrid systems. Non-standard analysis is an extension of classical analysis in which infinitesimal (the ε and η   in the celebrated generic sentence ∀ε∃η…∀ε∃η… of college maths) can be manipulated as first class citizens. This approach allows us to define both a denotational semantics, a constructive semantics, and a Kahn Process Network semantics for hybrid systems, thus establishing simulation engines on a sound but flexible mathematical foundation. These semantics offer a clear distinction between the concerns of the numerical analyst (solving differential equations) and those of the computer scientist (generating execution schemes). We also discuss a number of practical and fundamental issues in hybrid system modelers that give rise to non-reproducibility of results, non-determinism, and undesirable side effects. Of particular importance are cascaded mode changes (also called “zero-crossings” in the context of hybrid systems modelers).

► Hybrid systems modelers: semantics, compilation, scheduling of zero-crossings. ► Non-standard semantics for hybrid systems, using infinitesimal base step. ► Constructive semantics à la Berry and Kahn actor semantics of hybrid systems. ► Using the above semantics to handle cascaded zero-crossings. ► Using the above semantics to slice compilation into discrete and continuous parts.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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