Design and implementation of a knowledge-based framework for the modelling and simulation of hybrid systems
Design and implementation of a knowledge-based framework for the modelling and simulation of hybrid systems
- Author(s): D.A. Linkens and E.B. Tanyi
- DOI: 10.1049/cp:19960607
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- Author(s): D.A. Linkens and E.B. Tanyi Source: UKACC International Conference on Control. Control '96, 1996 p. 527 – 532
- Conference: UKACC International Conference on Control. Control '96
- DOI: 10.1049/cp:19960607
- ISBN: 0 85296 666 0
- Location: Exeter, UK
- Conference date: 2-5 Sept. 1996
- Format: PDF
The paper describes a knowledge-based framework for the modelling and simulation of hybrid systems and its implementation in the G2 Expert System tool. The approach is based on three key notions : a hybrid model base, hybrid simulation, and interactions between dissimilar model elements. The hybrid model base is a repository of model building paradigms, including Grafcets, equations, rules, and object-orientation. Hybrid simulation is based on the concurrent execution of the G2 continuous simulator, a Grafcet simulator, and the G2 inference engine. The three simulators exchange information through interactions which are dynamically created during a simulation. Interactions are modelled as notional objects with attributes specifying the variables and variable types involved in the exchange of information. This represents a form of causality between the source and receptor variables. The approach is illustrated by applying it to the modelling and simulation of a rolling mill.
Inspec keywords: inference mechanisms; object-oriented methods; industrial control; digital simulation
Subjects: Simulation techniques; Control engineering computing; Knowledge engineering techniques; Object-oriented programming
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