Applications: Industry and Education

Co-Chair Pieter J. Mosterman
Real-time and Simulation Technologies
The MathWorks, Inc.
Co-Chair Jin-Shyan Lee
Department of Electrical and Control Engineering
National Chiao-Tung University
Taiwan, ROC

For more pictures of the session, please click here.

Lee and Mosterman Over the last decades engineered systems have reached a tremendous level of complexity, involving expertise from many disciplines and entailing a variety of implementation technologies (e.g., embedded software, microelectromechanical systems, analog circuits, and digital circuits). The heterogeneous nature of these systems invariably combines with an architecture of different concurrent components that interact through continuous signals or discrete message passing. The corresponding increased level of complexity has led to the use of more formal approaches to system design through realization. Efficient and effective approaches apply dedicated modeling formalisms to different aspects of the system. Consequently, the complete system specification process combines several modeling, design, implementation, and realization paradigms (e.g., differential equation modeling, continuous time signal processing, and discrete event controllers) and decomposition of the entire specification task allows teams of experts to concurrently work on their domain of expertise. In the area of computer aided control system design this includes, e.g., control system design, simulation, optimization, modeling, and verification.

Lee and Mosterman Specialized computer automated tools for each of these domains are very helpful or even indispensable to carry out the related tasks. However, because these tools hardly ever are compatible, the sharing and coordinating of information flow between project teams inevitably leads to a lot of overhead in terms of collaboration and is very error prone, inefficient, and expensive. Moreover, similar tasks may be carried out multiple times and even simultaneously. For example, compared to control design approaches, fault detection and isolation (FDI) methods often rely on different, more detailed, models of the same system, which, as a consequence, is modeled by the control design team as well as the FDI team.

Paper 1 [Simon Lacoste-Julien] discusses the ability to model and simulate complex physical as well as control systems. Appropriate modeling formalisms need to be available, depending on the type of system under study, on the aspects of the structure and behaviour of the system one is interested in, and on the kind of queries one wishes to make regarding the system. This paper presents a hybrid formalism that combines event-scheduling with ordinary differential equations. It shows how meta-modelling, the explicit modelling of a class of models, can be used to describe the syntax of the hybrid formalism. Simulation of a Personalized Rapid Transit vehicle is shown to consist of a series of model transformations, modeled by graph grammars, that modify time as well as the state.

Paper 2 [Hugh H. T. Liu] demonstrates the usage of a multi-paradigm simulation framework for the requirement validation and verification of fly-by-wire (FBW) flight control systems. The requirement validation and verification (V&V) is an integrated part of systems engineering process, across different development stages. In the meantime, simulation has been used quite extensively in aircraft development and seems promising to serve as a tool in V&V. In order to make the requirements and validation criteria consistent at different development phases, teams that often use different simulation platforms, multi-paradigm modeling and simulation strategy will come to play an important role. This paper presents preliminary investigation in FBW flight control system V&V using a proposed multi-paradigm simulation framework.

Paper 3 [Luciano Baresi] The correct behavior of hybrid systems depends on the interactions between time-continuous and time-discrete subsystems, e.g., a time-continuous plant and a time-discrete control. Complex interaction patterns can be verified only with models that integrate both types of subsystems. This paper presents a tool that uses Matlab/Simulink for modeling time-continuous plants and timed Petri nets for modeling time-discrete controls, and support the verification of the system design through integrated simulation of the models. The control subsystem is specified with an IEC-compliant PLC editor integrated in Matlab/Simulink. The tool automatically maps IEC 61131-3 FBD specifications into timed Petri nets and integrates obtained models with the Simulink models of the plant to allow for simulating the whole system based on event driven discretization of the time-continuous components.

Paper 4 [Jin-Shyan Lee] In the past years, modeling and simulation of hybrid dynamic systems (HDS) have attracted much attention. However, since simultaneously dealing with the discrete and continuous variables is very difficult, most of the models result in a unified, but more complicated and unnatural format. Moreover, design engineers cannot be allowed to use their preferred domain models. Based on the multi-paradigm modeling (MPaM) concept, this paper proposed a Petri net (PN) framework with associated state equations to model the HDS. In the presented approach, modeling schemes of the hybrid systems are separated, but combined in a hierarchical way through specified interfaces. Designers can still work in their familiar domain-specific modeling paradigms and the heterogeneity is hidden when composing large systems. An application to a rapid thermal process (RTP) in semiconductor manufacturing is provided to demonstrate the practicability of the developed approach.

Paper 5 [Fernando Barros] Complex systems exhibiting structural changes can be better represented by models that can mimic these transformations. The Heterogeneous Flow System Specification (HFSS) is a comprehensive formalism that can represent a large variety of models using a unifying representation. The HFSS formalism represents models in a hierarchical and modular form. The explicit representation of structure makes possible to alter it dynamically. Among hybrid models, the most important include digital controllers and hybrid integrators. The HFSS ability to provide a common ground to represent these elements permits to model complex systems in a simple framework. We present a detailed model of a PID controller and we show how this digital controller can be merged with other types of components. To illustrate formalism application we model a 2-stage rocket system, whose velocity is set by a PI digital controller, by a dynamic structure network of hybrid components. Simulation results for the rocket system are presented.

Paper 6 [Klaus D. Mueller-Glaser] Up to 70 electronic control units (ECUs) serve for safety and comfort functions in a car. Communicating over different bus systems most ECU's perform closed loop control functions and reactive functions and have to fulfill hard real time constraints. The challenge for the design of those distributed and networked control units is to define all requirements and constraints, understand and analyze those manifold interactions between the control units, the car and the environment (driver, road, weather) in normal as well as stress situations (crash). To design within a development process which is concurrent and distributed between the automotive manufacturer and several suppliers requires a well understood life-cycle model, a strictly controlled design methodology and using computer aided engineering tools to its largest extent. The CASE-tool integration platform "GeneralStore" has been developed to support the design of automotive ECU's. In addition, GeneralStore is also used for the design of industrial automation systems and biomedical systems.

"Meta-Modelling Hybrid Formalisms", slides
Simon Lacoste-Julien
Computer Science Division, University of California, Berkeley, CA
Hans Vangheluwe
School of Computer Science, McGill University, Montreal, Canada
Juan de Lara
Departamento de Ingeniería Informática, Universidad Autónoma de Madrid, Spain
Pieter J. Mosterman
The MathWorks, Inc., Natick, MA

"Multiparadigm Design, Validation and Verification by Simulation in Flight Control System Development", slides
Hugh H. T. Liu
Institute for Aerospace Studies, University of Toronto, Toronto, Canada

"On Verifying Hybrid Systems with Simulink and Timed Petri Nets"1
Luciano Baresi
Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy
Marco Mauri
Dipartimento di Meccanica, Politecnico di Milano, Milano, Italy
Mauro Pezzč
Dipartimento di Informatica, Sistemistica e Comunicazione, Universitŕ degli Studi di Milano Bicocca

"A Multi-Paradigm Modeling Approach for Hybrid Dynamic Systems", slides
Jin-Shyan Lee
Department of Electrical and Control Engineering, National Chiao-Tung University, Hsinchu, Taiwan
Meng-Chu Zhou
Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ
Pau-Lo Hsu
Department of Electrical and Control Engineering, National Chiao-Tung University, Hsinchu, Taiwan

"Modeling and Simulation of Digital Controllers for Hybrid Dynamic Structure Systems",2 slides
Fernando J. Barros
Dept. Eng. Informática, Universidade de Coimbra, Coimbra, Portugal

"Heterogeneous Modeling for Automotive Electronic Control Units using a CASE-Tool Integration Platform", slides
Klaus D. Müller-Glaser, Clemens Reichmann, Philipp Graf
Institut für Technik der Informationsverarbeitung, University of Karlsruhe, Karlsruhe, Germany
Markus Kühl, and Klaus Ritter
Forschungszentrum Informatik, Karlsruhe, Germany

1This is the version of the paper submitted for review. It was not presented at the symposium.
2This paper was presented at the Conference on Conceptual Modeling and Simulation, Genoa, Italy, October 28-30, 2004, and published in its proceedings.

Home Special Issues Workshops Invited Sessions References
The Inaugural Bellairs workshop
Heterogeneous Modeling
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Behavior Generation
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Domain Specific Modeling
1st Multi-Paradigm Modeling: Concepts and Tools
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CAMPaM Tools
2nd Multi-Paradigm Modeling: Concepts and Tools
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33d Multi-Paradigm Modeling: Concepts and Tools