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

  • Sven Burmester
  • Holger GieseEmail author
  • Eckehard Münch
  • Oliver Oberschelp
  • Florian Klein
  • Peter Scheideler
Secial Section SFB 614


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.


Multi-agent systems Mechatronic Self-optimization Control Hybrid systems Components Reconfiguration UML Real-time 


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  1. 1.
    Alur, R., Courcoubetis, C., Halbwachs, N., Henzinger, T., Ho, P.H., Nicollin, X., Olivero, A., Sifakis, J., Yovine, S.: The algorithmic analysis of hybrid systems. Theor. Comput. Sci. 138(3–34) (1995)Google Scholar
  2. 2.
    Alur, R., Dang, T., Esposito, J., Fierro, R., Hur, Y., Ivancic, F., Kumar, V., Lee, I., Mishra, P., Pappas, G., Sokolsky, O.: Hierarchical hybrid modeling of embedded systems. In: Proceedings of the 1st Workshop on Embedded Software (2001)Google Scholar
  3. 3.
    Awad, M., Kuusela, J., Ziegler, J.: Object-Oriented Technology for Real-Time Systems: A Practical Approach Using OMT and Fusion. Prentice Hall, Enlewood cliffs (1996)Google Scholar
  4. 4.
    Bauer, B., Müller, J.P.: Using UML in the context of agent- oriented software engineering: State of the art. In: Agent-Oriented Software Engineering IV. LNCS, vol. 2935, pp. 1–24. Springer, Heidelberg (2003)Google Scholar
  5. 5.
    Bauer, B., Müller, J.P., Odell, J.: Agent UML: a Formalism for specifying multiagent interaction. In: Ciancarini, P., Wooldridge, M. (eds.) Workshop on Agent-Oriented Software Engineering (Held at the 22nd International Conference on Software Engineering (ISCE2000)), pp. 91–103. Springer, Heidelberg (2001)Google Scholar
  6. 6.
    Bender, K., Broy, M., Peter, I., Pretschner, A., Stauner, T.: Model based development of hybrid systems. In: Modelling, Analysis, and Design of Hybrid Systems. Lecture Notes on Control and Information Sciences, vol. 279, pages 37–52 Springer, Heidelberg (2002)Google Scholar
  7. 7.
    Bichler, L., Radermacher, A., Schuerr, A.: Evaluating UMl Extensions for Modeling Real-Time Systems. In: Proceedings of the 7th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems (WORDS 2002), pp. 271ff, San Diego (2002)Google Scholar
  8. 8.
    Bollella, G., Brosgol, B., Furr, S., Hardin, S., Dibble, P., Gosling, J., Turnbull, M.: The Real-Time Specification for JavaTM. Addison-Wesley, (2000)Google Scholar
  9. 9.
    Bradley, D., Seward, D., Dawson, D., Burge, S.: Mechatronics. Stanley Thornes (2000)Google Scholar
  10. 10.
    Brooks, R.A.: Intelligence without reason. In: Myopoulos, J., Reiter, R. (eds) Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI-91), pp. 569–595, Sydney, Morgan Kaufmann publishers Inc., San MateoGoogle Scholar
  11. 11.
    Burmester, S., Gehrke, M., Giese, H., Oberthür, S.: Making mechatronic agents resource-aware in order to enable safe dynamic resource allocation. In: Proceedings of 4th ACM International Conference on Embedded Software 2004 (EMSOFT 2004), Pisa, ACM, (2004)Google Scholar
  12. 12.
    Burmester, S., Giese, H., Gambuzza, A., Oberschelp, O.: Partitioning and modular code synthesis for reconfigurable mechatronic software components. In: Proceedings of European Simulation and Modelling Conference (ESMc’2004), Paris (2004)Google Scholar
  13. 13.
    Burmester, S., Giese, H., Oberschelp, O.: Hybrid UML components for the design of complex self-optimizing mechatronic systems. In: Proceedings of 1st International Conference on Informatics in Control, Automation and Robotics (ICINCO 2004), Setubal, IEEE, Washington (2004)Google Scholar
  14. 14.
    Burmester, S., Giese, H., Schäfer, W.: Model-driven architecture for hard real-time systems: from platform independent models to code. In: Proceedings of the European Conference on Model Driven Architecture—Foundations and Applications (ECMDA-FA’05), Nürnberg, LNCS, vol. 3748, pp. 1–15. Springer, Heidelberg (2005)Google Scholar
  15. 15.
    Burmester, S., Giese, H., Tichy, M.: Model-driven development of reconfigurable mechatronic systems with mechatronic UML. In Model Driven Architecture: Foundations and Applications, LNCS, vol. 3599, pp. 47–61. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    Cotting, M.C., Burken, J.J.: Reconfigurable control design for the full x-33 flight envelope. Technical report, NASA Dryden Flight Research Center Edwards, California (2001)Google Scholar
  17. 17.
    Douglass, B.P.: Real-Time UML: Developing Efficient Objects for Embedded Systems, 2nd edn. The Addison-Wesley Object Technology Series. Addison-Wesley, Reading (1999)Google Scholar
  18. 18.
    Ferber, J.: Multi-agent systems : an introduction to distributed artificial intelligence. Addison-Wesley, Reading (1999)Google Scholar
  19. 19.
    Ferguson, I.A.: Touringmachines: autonomous agents with attitudes. IEEE Comput. 25(5), 51–55 (1992)MathSciNetGoogle Scholar
  20. 20.
    Giese, H., Burmester, S., Klein, F., Schilling, D., Tichy, M.: Multi-agent system design for safety-critical self-optimizing mechatronic systems with UML. In: OOPSLA 2003—2nd International Workshop on Agent-Oriented Methodologies, Anaheim, pp. 21–32 (2003)Google Scholar
  21. 21.
    Giese, H., Burmester, S., Schäfer, W., Oberschelp, O.: Modular design and verification of component-based mechatronic systems with online-reconfiguration. In: Proceedings of 12th ACM SIGSOFT Foundations of Software Engineering 2004 (FSE 2004), Newport Beach, ACM, New York (2004)Google Scholar
  22. 22.
    Giese, H., Tichy, M., Burmester, S., Schäfer, W., Flake, S.: Towards the compositional verification of real-time UML designs. In: Proceedings of ESEC/FSE, Helsinki, pp. 38–47. ACM Press, New York (2003)Google Scholar
  23. 23.
    Gomaa, H.: Designing Concurrent, Distributed, and Real-Time Applications with UML. Addison-Wesley, Reading (2000)Google Scholar
  24. 24.
    Grosu, R., Stauner, T., Broy, M.: A modular visual model for hybrid systems. In: Proceedings of Formal Techniques in Real-Time and Fault-Tolerant Systems (FTRTFT’98). LNCS, vol. 1486. Springer, Heidelberg (1998)Google Scholar
  25. 25.
    Gu, Z., Kodase, S., Wang, S., Shin, K.G.: A model-based approach to system-level dependency and real-time analysis of embedded software. In: The 9th IEEE Real-Time and Embedded Technology and Applications Symposium, Toronto (2003)Google Scholar
  26. 26.
    Henzinger, T.A.: Masaccio: a Formal model for embedded components. In: Proceedings of the 1st IFIP International Conference on Theoretical Computer Science (TCS). LNCS, vol. 1872, Springer, Heidelberg (2000)Google Scholar
  27. 27.
    Henzinger, T.A., Ho, P.-H., Wong-Toi, H.: HyTech: the next generation. In: Proceedings of the 16th IEEE Real-Time Symposium. IEEE Computer Press, Piscataway (1995)Google Scholar
  28. 28.
    Henzinger, T.A., Minea, M., Prabhu, V.: Assume-guarantee reasoning for hierarchical hybrid systems. In: Proceedings of the 4th International Workshop on Hybrid Systems: Computation and Control (HSCC 2001), Rome. LNCS, vol. 2034, pp. 275–290. Springer, Heildelberg (2001)Google Scholar
  29. 29.
    Hestermeyer, T., Münch, E., Oberschelp, O.: Sollbahn—Planung für schienengebundene Fahrzeuge. In: Berechnung und Simulation im Fahrzeugbau 2004, Würzburg, VDI (2004)Google Scholar
  30. 30.
    Hestermeyer, T., Oberschelp, O., Giese, H.: Structured information processing for self-optimizing mechatronic systems. In: Proceedings of 1st International Conference on Informatics in Control, Automation and Robotics (ICINCO 2004), Setubal, Portugal. IEEE, Washington (2004)Google Scholar
  31. 31.
    Honekamp, U.: IPANEMA—Verteilte Echtzeit-Informationsverarbeitung in mechatronischen Systemen. PhD thesis, Universität Paderborn, Düsseldorf (1998)Google Scholar
  32. 32.
    Isermann, R., Lachmann, K.-H., Matko, D.: Adaptive Control Systems. Prentice Hall, Hertfordshire (1992)zbMATHGoogle Scholar
  33. 33.
    Kapinski, J., Krogh, B.: Verifying switched-mode computer controlled systems. In: Computer Aided Control System Design. IEEE Control Systems Society, Washington (2002)Google Scholar
  34. 34.
    Kesten, Y., Pnueli, A.: Timed and hybrid statecharts and their textual representation. In: Proceedings of Formal Techniques in Real-Time and Fault-Tolerant Systems, 2nd International Symposium, LNCS, vol. 571. Springer, Heidelberg (1992)Google Scholar
  35. 35.
    Kühl, M., Reichmann, C., Prötel, I., Müller-Glaser, K.D.: From object-oriented modeling to code generation for rapid prototyping of embedded electronic systems. In: Proceedings of the 13th IEEE International Workshop on Rapid System Prototyping (RSP’02), Darmstadt, Heidelberg (2002)Google Scholar
  36. 36.
    Lamport, L.: Hybrid systems in tla+. Springer, Heidelberg (1993)Google Scholar
  37. 37.
    Larsen, K., Pettersson, P., Yi, W.: UPPAAL in a Nutshell. Springer Int. J. Softw. Tools Technol 1(1) (1997)Google Scholar
  38. 38.
    Li, P.Y., Horowitz, R.: Self-optimizing control. In: Proceedings of the 36th IEEE Conference on Decision and Control (CDC), pp. 1228–1233, San Diego (1997)Google Scholar
  39. 39.
    Lynch, N., Segala, R., Vaandrager, F.: Hybrid I/O Automata Revisited. In: Proceedings of the 4th International Workshop on Hybrid Systems: Computation and Control (HSCC 2001), Rome LNCS, vol. 2034, pp. 403–417. Springer, Heidelberg (2001)Google Scholar
  40. 40.
    Masse, J., Kim, S., Hong, S.: Tool set implementation for scenario-based multithreading of UML-RT models and experimental validation. In: The 9th IEEE Real-Time and Embedded Technology and Applications Symposium, Toronto (2003)Google Scholar
  41. 41.
    McKinley, P.K., Sadjadi, S.M., Kasten, E.P., Cheng, B.H.: Composing Adaptive Software. IEEE Comput. 37(7) (2004)Google Scholar
  42. 42.
    Münch, E., Oberschelp, O., Hestermeyer, T., Scheideler, P., Schmidt, A.: Distributed optimization of reference trajectories for active suspension with multi-agent systems. In: 18th European Simulation Multiconference (ESM), Magdeburg, VDI (2004)Google Scholar
  43. 43.
    Naumann, R., Rasche, R.: Description and simulation of hybrid mechatronic systems. In: International Workshop on Hybrid Systems: Computation and Control, Berkeley (1998)Google Scholar
  44. 44.
    Oberschelp, O., Gambuzza, A., Burmester, S., Giese, H.: Modular generation and simulation of mechatronic systems. In: Proceedings of the 8th world multi-conference on systemics, cybernetics and informatics (SCI), Orlando (2004)Google Scholar
  45. 45.
    Oberschelp, O., Hestermeyer, T., Kleinjohann, B., Kleinjohann, L.: Design of self-optimizing agent-based controllers. In CfP Workshop 2002—Agent-Based Simulation 3, Passau (2002)Google Scholar
  46. 46.
    Object Management Group. UML Profile for Schedulability, Performance, and Time Specification. OMG Document ptc/02-03-02 (2002)Google Scholar
  47. 47.
    Object Management Group. UML for System Engineering Request for Proposal, ad/03-03-41 (2003)Google Scholar
  48. 48.
    Object Management Group. UML 2.0 Superstructure Specification. (2004)Google Scholar
  49. 49.
    Ogata, K.: Modern Control Engineering. Prentice Hall, Englewood cliff (2002)Google Scholar
  50. 50.
    Parunak, H.V.D., Odell, J. Representing social structures in UML. In: Müller, J.P., Andre, E., Sen, S., Frasson, C. (eds.) Proceedings of the 5th International Conference on Autonomous Agents, Montreal, pp. 100–101, ACM Press, New YorkGoogle Scholar
  51. 51.
    Poggi, A., Rimassa, G., Turci, P., Odell, J., Mouratidis, H., Manson, G.: Modeling deployment and mobility issues in multiagent systems using AUML. In: Agent-Oriented Software Engineering IV, 4th International Workshop, AOSE 2003, Melbourne, Revised Papers. LNCS, vol. 2935, pp. 69–84. Springer, Heidelberg (2003)Google Scholar
  52. 52.
    Selic, B., Gullekson, G., Ward, P.: Real-Time Object-Oriented Modeling. Wiley, London (1994)zbMATHGoogle Scholar
  53. 53.
    Selic, B., Rumbaugh, J.: Using UML for modeling complex real-time systems. Technical report, ObjecTime Limited (1998)Google Scholar
  54. 54.
    Stauner, T.: Systematic Development of Hybrid Systems. PhD thesis, Technische Universität München (2001)Google Scholar
  55. 55.
    Stauner, T., Pretschner, A., Péter, I.: Approaching a discrete- continuous UML: tool support and formalization. In: Proceedings of the UML’2001 workshop on Practical UML-Based Rigorous Development Methods—Countering or Integrating the eXtremists, Toronto, pp. 242–257 (2001)Google Scholar
  56. 56.
    Storey, N.: Safety-Critical Computer Systems. Addison-Wesley, Reading (1996)Google Scholar
  57. 57.
    SysML Partners. Systems Modeling Language: SysML (2005)Google Scholar
  58. 58.
    Wagner, G.: The agent-object-relationship metamodel: towards a unified view of state and behavior. Info. Syst. 28(5), 475–504 (2003)zbMATHCrossRefGoogle Scholar
  59. 59.
    Wieting, R.: Hybrid high-level nets. In: Proceedings of the 1996 Winter Simulation Conference, Coronado, pp. 848–855 (1996)Google Scholar
  60. 60.
    Wooldridge, M.: An Introduction to Multiagent Systems. Wiley, Chichester (2002)Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Sven Burmester
    • 1
  • Holger Giese
    • 2
    Email author
  • Eckehard Münch
    • 3
  • Oliver Oberschelp
    • 3
  • Florian Klein
    • 1
  • Peter Scheideler
    • 4
  1. 1.Software Engineering Group, Department of Computer Science supported by the International Graduate School of Dynamic Intelligent SystemsUniversity of PaderbornPaderbornGermany
  2. 2.System Analysis and Modeling GroupHasso Plattner Institute, University of PotsdamPotsdamGermany
  3. 3.Control Engineering and MechatronicsUniversity of PaderbornPaderbornGermany
  4. 4.Heinz Nixdorf InstituteUniversity of PaderbornPaderbornGermany

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