Non-standard semantics of hybrid systems modelers

被引:37
作者
Benveniste, Albert [1 ]
Bourke, Timothy [1 ]
Caillaud, Benoit [1 ]
Pouzet, Marc [2 ]
机构
[1] INRIA Rennes, F-35042 Rennes, France
[2] Ecole Normale Super, F-75005 Paris, France
关键词
Hybrid systems; Hybrid systems modelers; Non-standard analysis; Non-standard semantics; Constructive semantics; Kahn process networks; Compilation of hybrid systems; SYNCHRONOUS LANGUAGES;
D O I
10.1016/j.jcss.2011.08.009
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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 epsilon and eta in the celebrated generic sentence for all epsilon there exists eta ... 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). (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:877 / 910
页数:34
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