A multi-agent methodology for multi-level modeling of mechatronic systems

Mechatronic design aims to integrate the models developed during the mechatronic design process, in order to be able to optimize the overall mechatronic system performance. A lot of work has been done in the last few years by researchers and software developers to achieve this objective. However, the level of integration does not yet meet the purposes of mechatronic system designers, particularly when dealing with modeling changes. Therefore, new methodologies are required to manage the multi-view complexity of mechatronic design. In this paper, we propose a multi-agent methodology for the multi-abstraction modeling issue of mechatronic systems. The major contribution deals with proposing a new method for the decomposition of the multi-level design into agents linked with relationships. Each agent is representing an abstraction level and both agent and relationships are managed with rules. By considering an application to a piezoelectric energy harvesting system, we show how we associate agents, rules and inter-level relationships to multi-abstraction modeling. We also show how modeling errors are identified using this approach.

[1]  Rajit Gadh,et al.  Geometric shape abstractions for internet-based virtual prototyping , 1998, Comput. Aided Des..

[2]  Jan F. Broenink,et al.  Multi-view methodology for the design of embedded mechatronic control systems , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[3]  Olivia Penas,et al.  Layout optimization of power modules using a sequentially coupled approach , 2011 .

[4]  Carlos Angel Iglesias Fernandez,et al.  A survey of agent-oriented methodologies , 1999 .

[5]  Stephen P. Timoshenko,et al.  Vibration problems in engineering , 1928 .

[6]  Franco Zambonelli,et al.  Organisational Rules as an Abstraction for the Analysis and Design of Multi-Agent Systems , 2001, Int. J. Softw. Eng. Knowl. Eng..

[7]  J. Amerongen Mechatronic design , 2003 .

[8]  Michael Wooldridge,et al.  Agent-based software engineering , 1997, IEE Proc. Softw. Eng..

[9]  Volume Su IEEE Standard on Piezoelectricity , 1984 .

[10]  Nicholas R. Jennings,et al.  A Roadmap of Agent Research and Development , 2004, Autonomous Agents and Multi-Agent Systems.

[11]  Moncef Hammadi,et al.  Contribution à l'intégration de la modélisation et la simulation multi-physique pour conception des systèmes mécatroniques, , 2012 .

[12]  Yuval Shahar,et al.  Dynamic temporal interpretation contexts for temporal abstraction , 1998, Annals of Mathematics and Artificial Intelligence.

[13]  R. B. Yates,et al.  Analysis Of A Micro-electric Generator For Microsystems , 1995, Proceedings of the International Solid-State Sensors and Actuators Conference - TRANSDUCERS '95.

[14]  Crispin Hales,et al.  Engineering design: a systematic approach , 1989 .

[15]  Levent Yilmaz,et al.  Synergies of simulation, agents, and systems engineering , 2012, Expert Syst. Appl..

[16]  D. Sorensen,et al.  A Survey of Model Reduction Methods for Large-Scale Systems , 2000 .

[17]  Jan Treur A Unified Specification Format for interlevel Relations between Agent Models in Multiple Abstraction Dimensions , 2013, Int. J. Model. Simul. Sci. Comput..

[18]  Chuan-Jun Su,et al.  Mobile multi-agent based, distributed information platform (MADIP) for wide-area e-health monitoring , 2008, Comput. Ind..

[19]  Levent Yilmaz,et al.  On the Synergy of Simulation and Agents: An Innovation Paradigm Perspective , 2009 .

[20]  Jim Hewit Mechatronics design - The key to performance enhancement , 1996, Robotics Auton. Syst..

[21]  Rolf Isermann,et al.  Modeling and design methodology for mechatronic systems , 1996 .

[22]  J. M. Noworolski,et al.  Generalized averaging method for power conversion circuits , 1990, 21st Annual IEEE Conference on Power Electronics Specialists.

[23]  Frédéric Boulanger,et al.  Exploring Multi-Paradigm Modeling Techniques , 2009, Simul..

[24]  Nils Ferrand,et al.  HOW A CONCEPTUAL FRAMEWORK CAN HELP TO DESIGN MODELS FOLLOWING DECREASING ABSTRACTION , 2001 .

[25]  Sang-Gook Kim,et al.  DESIGN CONSIDERATIONS FOR MEMS-SCALE PIEZOELECTRIC MECHANICAL VIBRATION ENERGY HARVESTERS , 2005 .

[26]  Afsaneh Haddadi,et al.  Application of multi-agent systems in traffic and transportation , 1997, IEE Proc. Softw. Eng..

[27]  James S. Coleman,et al.  Rational Choice Theory: Advocacy and Critique , 1992 .

[28]  Eithan Ephrati,et al.  Divide and Conquer in Multi-Agent Planning , 1994, AAAI.

[29]  Klaus Zeman,et al.  Consistency Checking of Mechatronic Design Models , 2010 .

[30]  Jan M. Rabaey,et al.  A study of low level vibrations as a power source for wireless sensor nodes , 2003, Comput. Commun..

[31]  Jan Keiser,et al.  Agent-based telematic services and telecom applications , 2001, CACM.

[32]  Weiming Shen,et al.  Applications of agent-based systems in intelligent manufacturing: An updated review , 2006, Adv. Eng. Informatics.

[33]  A. Antoulas,et al.  A Survey of Model Reduction by Balanced Truncation and Some New Results , 2004 .

[34]  Mieczyslaw Metzger,et al.  A Survey on Applications of Agent Technology in Industrial Process Control , 2011, IEEE Transactions on Industrial Informatics.

[35]  John E. Mottershead,et al.  Model Updating In Structural Dynamics: A Survey , 1993 .

[36]  Rudolf Scheidl,et al.  Model relations between conceptual and detail design , 2010 .

[37]  Daniel J. Inman,et al.  Piezoelectric Energy Harvesting , 2011 .

[38]  Andy Schürr,et al.  Model-driven systems engineering: state-of-the-art and research challenges , 2010 .

[39]  Jeff A. Estefan,et al.  of Model-Based Systems Engineering ( MBSE ) Methodologies , 2008 .

[40]  Carlos Angel Iglesias,et al.  A Survey of Agent-Oriented Methodologies , 1998, ATAL.