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A Fuzzy Control Method for Priority Driven Embedded Device

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Proceedings of the Third International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’18) (IITI'18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 874))

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Abstract

The current goal is to minimize an embedded system consumption while maintaining all its features. Well-tuned power management becomes even more important in systems without any possibility of energy harvesting that rely solely on the battery power. The aim is a significant increase in the battery life without a desirable degradation in the quality of the service.

A fuzzy rule-based classifier is intended to secure a simulation of the priority of the operation and the battery voltage. The energy consumption is a critical concern in the battery operated embedded devices. Power management is one of the most important consider aspects in low-power embedded systems design.

This contribution studies the low power system in terms of the battery voltage level, depending on system priorities. The goal is to achieve the best possible efficiency of a whole device. The article offers a list of arrangements and applied methods having the most significant impact on the extension of the systems operating time.

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References

  1. Cocaña-Fernández, A., Ranilla, J., Gil-Pita, R., Sánchez, L.: Energy-conscious fuzzy rule-based classifiers for battery operated embedded devices. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1–6. IEEE (2017)

    Google Scholar 

  2. Gao, C., Zhao, J., Wu, J., Hao, X.: Optimal fuzzy logic based energy management strategy of battery/supercapacitor hybrid energy storage system for electric vehicles. In: 2016 12th World Congress on Intelligent Control and Automation (WCICA), pp. 98–102. IEEE (2016)

    Google Scholar 

  3. Kandel, A.: Fuzzy Expert Systems. CRC Press, Boca Raton (1991)

    MATH  Google Scholar 

  4. Kansal, A., Hsu, J., Zahedi, S., Srivastava, M.B.: Power management in energy harvesting sensor networks. ACM Trans. Embed. Comput. Syst. 6(4), 1–38 (2007)

    Article  Google Scholar 

  5. Kromer, P., Prauzek, M., Musilek, P.: Harvesting-aware control of wireless sensor nodes using fuzzy logic and differential evolution. In: 2014 11th Annual IEEE International Conference on Sensing, Communication, and Networking Workshops, SECON Workshops 2014, pp. 51–56 (2014)

    Google Scholar 

  6. Lan, C., Lin, S., Syue, S., Hsu, H., Huang, T., Tan, K.: Development of an intelligent lithium-ion battery-charging management system for electric vehicle. In: Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017, pp. 1744–1746 (2017)

    Google Scholar 

  7. Linlin, L., Xu, Z., Zhujinsheng, Jing, X., Shuntao, X.: Research on dynamic equalization for lithium battery management system. In: Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017, pp. 6884–6888 (2017)

    Google Scholar 

  8. MacKo, D., Jelemenska, K., Cicak, P.: Early-stage verification of power-management specification in low-power systems design. In: Formal Proceedings of the 2016 IEEE 19th International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2016 (2016)

    Google Scholar 

  9. Musilek, P., Prauzek, M., Kromer, P., Rodway, J., Barton, T.: Intelligent energy management for environmental monitoring systems, December 2017

    Google Scholar 

  10. Nayak, P., Devulapalli, A.: A fuzzy logic-based clustering algorithm for wsn to extend the network lifetime. IEEE Sens. J. 16(1), 137–144 (2016)

    Article  Google Scholar 

  11. Novak, V., Perfilieva, I., Mockor, J.: Mathematical Principles of Fuzzy Logic, vol. 517. Springer Science & Business Media, Berlin (2012)

    MATH  Google Scholar 

  12. Pimentel, D., Musilek, P.: Power management with energy harvesting devices. In: 2010 23rd Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–4, May 2010

    Google Scholar 

  13. Prabhakar, T., Devasenapathy, S., Jamadagni, H., Prasad, R.: Smart applications for energy harvested WSNs. In: 2010 2nd International Conference on COMmunication Systems and NETworks, COMSNETS 2010 (2010)

    Google Scholar 

  14. Prauzek, M., Konecny, J., Hamel, A., Hlavica, J.: Fuzzy energy management of autonomous weather station. IFAC-PapersOnLine 28(4), 226–229 (2015)

    Article  Google Scholar 

  15. Prauzek, M., Musilek, P., Watts, A.G.: Fuzzy algorithm for intelligent wireless sensors with solar harvesting. In: IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - IES 2014: 2014 IEEE Symposium on Intelligent Embedded Systems, Proceedings, pp. 1–7 (2014)

    Google Scholar 

  16. Prauzek, M., Watts, A.G., Musilek, P., Wyard-Scott, L., Koziorek, J.: Simulation of adaptive duty cycling in solar powered environmental monitoring systems. In: 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–6, May 2014

    Google Scholar 

  17. Pursley, D., Yeh, T.: High-level low-power system design optimization. In: 2017 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2017 (2017)

    Google Scholar 

  18. Rodway, J., Musilek, P., Lozowski, E., Prauzek, M., Heckenbergerova, J.: Pressure-based prediction of harvestable energy for powering environmental monitoring systems. In: 2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings, pp. 725–730 (2015)

    Google Scholar 

  19. Son, S., Jeon, Y., Baek, Y.: Design and implementation of low-power location tracking system based on IEEE 802.11. In: Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014, pp. 562–565 (2014)

    Google Scholar 

  20. Stankovic, J.A., He, T.: Energy management in sensor networks. Philos Trans. A Math. Phys. Eng. Sci. 370(1958), 52–67 (2012)

    Article  Google Scholar 

  21. Yousra, N., Samir, B.A.: Fuzzy multiprocessor architecture reconfiguration based on dynamic frequency scaling. In: 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), pp. 1–6. IEEE (2017)

    Google Scholar 

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Acknowledgement

This work was supported by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project, project number CZ.02.1.01/0.0/0.0/16_019/0000867 within the Operational Program Research, Development and Education s the project SP2018/160, “Development of algorithms and systems for control, measurement and safety applications IV” of Student Grant System, VSB-TU Ostrava.

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Authors and Affiliations

  1. Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, Ostrava-Poruba, 70833, Czech Republic

    Karolina Janosova, Michal Prauzek, Jaromir Konecny, Monika Borova & Martin Stankus

Authors
  1. Karolina Janosova
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  2. Michal Prauzek
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  3. Jaromir Konecny
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  4. Monika Borova
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  5. Martin Stankus
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Corresponding author

Correspondence to Karolina Janosova .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Rostov State Transport University, Rostov-on-Don, Russia

    Sergey Kovalev

  3. Bauman Moscow State Technical University, Moscow, Russia

    Valery Tarassov

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. Rostov State Transport University, Rostov-on-Don, Russia

    Andrey Sukhanov

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Janosova, K., Prauzek, M., Konecny, J., Borova, M., Stankus, M. (2019). A Fuzzy Control Method for Priority Driven Embedded Device. In: Abraham, A., Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Third International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’18). IITI'18 2018. Advances in Intelligent Systems and Computing, vol 874. Springer, Cham. https://doi.org/10.1007/978-3-030-01818-4_21

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