Abstract
Self-optimizing mechatronic systems have the ability to adjust their goals and behavior according to changes of the environment or system by means of complex real-time coordination and reconfiguration in the underlying software and hardware. In this paper we sketch a generic software architecture for mechatronic systems with self-optimization and outline which analogies between this architecture and the information processing in natural organisms exist. The architecture at first exploits the ability of its subsystems to adapt their resource requirements to optimize its performance with respect to the usage of available computational resources. Secondly, the architecture achieves, inspired by the acute stress response of a natural being, that in the case of an emergency it makes all recources available to address a given threat in a self-coordinated manner.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
S. Burmester, M. Gehrke, H. Giese, and S. Oberthür. Making Mechatronic Agents Resource-aware in order to Enable Safe Dynamic Resource Allocation. In B. Georgio, editor, Proc. of Fourth ACM International Conference on Embedded Software 2004 (EMSOFT 2004), Pisa, Italy, pages 175–183. ACM Press, September 2004.
S. Burmester, H. Giese, and M. Tichy. Model-Driven Development of Reconfigurable Mechatronic Systems with Mechatronic UML. In U. Assmann, A. Rensink, and M. Aksit, editors, Model Driven Architecture: Foundations and Applications, volume 3599 of Lecture Notes in Computer Science, pages 47–61. Springer Verlag, Aug. 2005.
W. B. Cannon. Bodily Changes in Pain, Hunger, Fear and Rage: An Account of Recent Research Into the Function of Emotional Excitement. Appleton-Century-Crofts, 1929.
I. A. Ferguson. Touringmachines: Autonomous agents with attitudes. IEEE Computer, 25(5):51–55, 1992.
U. Frank, H. Giese, F. Klein, O. Oberschelp, A. Schmidt, B. Schulz, H. Vöcking, and K. Witting. Selbstoptimierende Systeme des Maschinenbaus-Definitionen und Konzepte. Number Band 155 in HNI-Verlagsschriftenreihe. Bonifatius GmbH, Paderborn, Germany, first edition, Nov. 2004.
H. Giese, S. Burmester, W. Schäfer, and O. Oberschelp. Modular Design and Verification of Component-Based Mechatronic Systems with Online-Reconfiguration. In Proc. of 12th ACM SIGSOFT Foundations of Software Engineering 2004 (FSE 2004), Newport Beach, USA, pages 179–188. ACM Press, November 2004.
H. Giese, M. Tichy, S. Burmester, W. Schäfer, and S. Flake. Towards the Compositional Verification of Real-Time UML Designs. In Proc. of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering (ESEC/FSE-11), pages 38–47. ACM Press, September 2003.
A. Herkersdorf. Towards a framework and a design methodology for autonomic integrated systems. In M. Reichert, editor, Proceedings of the Workshop on Organic Computing, 2004.
T. Hestermeyer, O. Oberschelp, and H. Giese. Structured Information Processing For Self-optimizing Mechatronic Systems. In H. Araujo, A. Vieira, J. Braz, B. Encarnacao, and M. Carvalho, editors, Proc. of 1st International Conference on Informatics in Control, Automation and Robotics (ICINCO 2004), Setubal, Portugal, pages 230–237. INSTICC Press, Aug. 2004.
D. J. Musliner, R. P. Goldman, M. J. Pelican, and K. D. Krebsbach. Self-Adaptive Software for Hard Real-Time Environments. IEEE Inteligent Systems, 14(4), July/Aug. 1999.
S. Oberthür and C. Böke. Flexible resource management-a framework for self-optimizing real-time systems. In B. Kleinjohann, G. R. Gao, H. Kopetz, L. Kleinjohann, and A. Rettberg, editors, Proceedings of IFIP Working Conference on Distributed and Parallel Embedded Systems (DIPES’04), pages 177–186. Kluwer Academic Publishers, 23–26 Aug. 2004.
P. Oreizy, M. M. Gorlick, R. N. Taylor, D. Heimbigner, G. Johnson, N. Medvidovic, A. Quilici, D. S. Rosenblum, and A. L. Wolf. An Architecture-Based Approach to Self-Adaptive Software. IEEE Intelligent Systems, 14(3):54–62, May/June 1999.
A. Pottharst. Energieversorgung und Leittechnik einer Anlage mit Linearmotor getriebenen Bahnfahrzeugen. Dissertation, University of Paderborn, Powerelectronic and Electrical Drives, Dec. 2005.
T. Schöler and C. Müller-Schloer. An observer/controller architecture for adaptive reconfigurable stacks. In M. Beigl and P. Lukowicz, editors, ARCS, volume 3432 of Lecture Notes in Computer Science, pages 139–153. Springer, 2005.
J. Sztipanovits, G. Karsai, and T. Bapty. Self-adaptive software for signal processing. Commun. ACM, 41(5):66–73, 1998.
J. F. Vincent Decugis. Action selection in an autonomous agent with a hierarchical distributed reactive planning architecture. In Proceedings of the second international conference on Autonomous agents, pages 354–361. ACM Press, 1998.
M. Wirsing, editor. Report on the EU/NSF Strategic Workshop on Engineering Software-Intensive Systems, Edinburgh, GB, May 2004.
K. Witting, B. Schulz, A. Pottharst, M. Dellnitz, J. Böcker, and N. Fröhleke. A new approach for online multiobjective optimization of mechatronical systems. Accepted for Int. J. on Software Tools for Technology Transfer STTT (Special Issue on Self-Optimizing Mechatronic Systems), 2006.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 International Federation for Information Processing
About this paper
Cite this paper
Giese, H., Montealegre, N., Müller, T., Oberthür, S., Schulz, B. (2006). Acute Stress Response for Self-optimizing Mechatronic Systems. In: Pan, Y., Rammig, F.J., Schmeck, H., Solar, M. (eds) Biologically Inspired Cooperative Computing. BICC 2006. IFIP International Federation for Information Processing, vol 216. Springer, Boston, MA . https://doi.org/10.1007/978-0-387-34733-2_16
Download citation
DOI: https://doi.org/10.1007/978-0-387-34733-2_16
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-34632-8
Online ISBN: 978-0-387-34733-2
eBook Packages: Computer ScienceComputer Science (R0)