Tool support for the design of self-optimizing mechatronic multi-agent systems

Authors:
Sven Burmester;Holger Giese;Eckehard Münch;Oliver Oberschelp;Florian Klein;Peter Scheideler
Affiliations:
University of Paderborn, Software Engineering Group, Department of Computer Science supported by the International Graduate School of Dynamic Intelligent Systems, Paderborn, Germany;Hasso Plattner Institute, University of Potsdam, System Analysis and Modeling Group, Potsdam, Germany;University of Paderborn, Control Engineering and Mechatronics, Paderborn, Germany;University of Paderborn, Control Engineering and Mechatronics, Paderborn, Germany;University of Paderborn, Software Engineering Group, Department of Computer Science supported by the International Graduate School of Dynamic Intelligent Systems, Paderborn, Germany;University of Paderborn, Heinz Nixdorf Institute, Paderborn, Germany
Venue:
International Journal on Software Tools for Technology Transfer (STTT)
Year:
2008

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Abstract

Complex technical systems, such as mechatronic systems, can exploit networking as well as the computational power available today to achieve an automatic improvement of the technical system performance at run-time through self-optimization. To realize this vision, appropriate means for the design of such self-optimizing mechatronic systems are required. Well-established techniques and tools for the modeling of cognitive behavior, reflective behavior, and control behavior exist. However, to really enable self-optimization and its full potential, these different aspects have to be safely integrated in a manner that remains comprehensible to the designer. In this article, we present how this required integration has been realized at the semantic level by extending the unified modeling language (UML), and at the tool level by integrating the CAE tool CAMeL and the CASE tool Fujaba real-time tool suite. The presented Mechatronic UML approach supports the design of verifiable, complex, reconfigurable mechatronic systems using the multi-agent system metaphor.