Abstract
With the new prospects that are offered by the diffusion of the communication means on the one hand, and the abilities of the control engineering and science to model and handle different categories of systems belonging to a broad range of application fields on the other hand, it is easy to envisions the development of new applications in the future, where the dynamics and the information will be strongly dependent. For that reason, the study of the integration of control, communication and computation was considered, in a recent report on the future of control (Murray et al. in IEEE Control Syst. Mag. 23(2):20–33, 2003), as a major challenge research direction. The integrated study of control communication, and computation (Årzén et al. in 39th IEEE conference on decision and control, Sydney, Australia, 2000) becomes more important when the communication bandwidth or the processing power is limited. Communication and computing resource limitations are generally presented as being a common characteristic to an important range of embedded systems. The term embedded system refers to an electronic system, which is in close relationship to a physical system. Embedded systems are reactive systems: they must correctly respond to the stimuli of their physical environment. They are characterized by a given degree of autonomy, which often appears in the autonomy of the computational resources, and less frequently in the autonomy of the energy supply.
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Notes
- 1.
These two communication links are commonly called by uplink and downlink communication channels.
- 2.
NP-complete is the set of all decision problems whose solutions can be verified in polynomial time.
References
K.-E. Årzén, A. Cervin, Control and embedded computing: survey of research directions, in Proceedings of the 16th IFAC World Congress, Prague, Czech Republic, July 2005
K.-E. Årzén, A. Cervin, J. Eker, L. Sha, An introduction to control and real-time scheduling co-design, in 39th IEEE Conference on Decision and Control, Sydney, Australia, December 2000
G. Belanger, J. Speyer, S. Ananyev, D. Chichka, R. Carpenter, Decentralized control of satellite clusters under limited communication, in Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Providence, Rhode Island, USA, August 2004
A. Berlin, K. Gabriel, Distributed MEMS: new challenges for computation. IEEE Comput. Sci. Eng. Mag. 4(1), 12–16 (1997)
G.C. Buttazzo, Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications (Prentice Hall, New York, 1997)
R.M. Chalasani, Ride performance potential of active suspension systems—Part II: comprehensive analysis based on a full-car model, in Proceedings of the Symposium on Simulation and Control of Ground Vehicles and Transportation Systems, ASME AMD, Anaheim, CA, USA, December 1986
M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness (Freeman, New York, 1979)
HYCON2. Prospective en automatique. Technical report, GDR MACS, December 2011
M. Kuschel, P. Kremer, S. Hirche, M. Buss, Lossy data reduction methods for haptic telepresence systems, in Proceedings of the IEEE International Conference on Robotics and Automation, Orlando, Florida, USA, May 2006
F.L. Lian, J.R. Moyne, D.M. Tilbury, Performance evaluation of control networks: Ethernet, ControlNet, and DeviceNet. IEEE Control Syst. Mag. 21(1), 66–83 (2001)
R.M. Murray, K.J. Åström, S. Boyd, R.W. Brockett, G. Stein, Future directions in control in an information-rich world. IEEE Control Syst. Mag. 23(2), 20–33 (2003)
N. Navet, Y. Song, F. Simonot-Lion, C. Wilwert, Trends in automotive communication systems. Proc. IEEE 93(6), 1204–1223 (2005)
A. Quazi, W. Konrad, Underwater acoustic communications. IEEE Commun. Mag. 20(2), 24–30 (1982)
A. Rachid, F. Collet, Bus CAN, in Techniques de l’Ingénieur—Traité Informatique Industrielle, vol. S 8 140 (Editions Techniques de l’Ingéieur, Paris, 2000)
B. Sinopoli, C. Sharp, L. Schenato, S. Schaffert, S.S. Sastry, Distributed control applications within sensor networks. Proc. IEEE 91(8), 1235–1246 (2003)
E. Sozer, M. Stojanovic, J. Proakis, Underwater acoustic networks. IEEE J. Ocean. Eng. 25(1), 72–83 (2000)
A. Speranzon, J. Silva, J. de Sousa, K.H. Johansson, On collaborative optimization and communication for a team of autonomous underwater vehicles, in Proceedings of Reglermöte, Stockholm, Sweden, May 2004
M. Stojanovic, Recent advances in high-speed underwater acoustic communications. IEEE J. Ocean. Eng. 21(2), 125–136 (1996)
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Çela, A., Ben Gaid, M., Li, XG., Niculescu, SI. (2014). Introduction to Distributed Control and Embedded Systems (DCES). In: Optimal Design of Distributed Control and Embedded Systems. Communications and Control Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-02729-6_1
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