The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

A Gaussian Approach in Stabilizing Outputs of Electrical Control Systems

전기제어 설비의 출력 안정화를 위한 가우시안 접근법

  • Basnet, Barun (Major of IT Applied System Engineering of Convergence Technology Engineering Division, Chonbuk National University) ;
  • Bang, Jun-ho (Major of IT Applied System Engineering of Convergence Technology Engineering Division, Chonbuk National University) ;
  • Ryu, In-ho (Major of IT Applied System Engineering of Convergence Technology Engineering Division, Chonbuk National University) ;
  • Kim, Tae-hyeong (Major of IT Applied System Engineering of Convergence Technology Engineering Division, Chonbuk National University)
  • Received : 2018.09.22
  • Accepted : 2018.10.05
  • Published : 2018.11.01
Download PDF
⟨ Previous Next ⟩

Abstract

Sensor readings always have a certain degree of randomness and fuzziness due to its intrinsic property, other electronic devices in the circuitry, wires and the rapidly changing environment. In an electrical control system, such readings will bring instability in the system and other undesired events especially if the signal hovers around the threshold. This paper proposes a Gaussian-based statistical approach in stabilizing the output through sampling the sensor data and automatic tuning the threshold to the range of multiple standard deviations. It takes advantage of the Central limit theorem and its properties assuming that a large number of sensor data samples will eventually converge to a Gaussian distribution. Experimental results demonstrate the effectiveness of the proposed algorithm in completely stabilizing the outputs over known filtering algorithms like Exponential smoothing and Kalman Filter.

Keywords

References

  1. A. Crespo, P. Albertos and J. Simo, "Embedded Control Systems: From Design to Implementation", Symp. Cost Oriented Automation, La Habana, Cuba, Feb. 2007.
  2. T. Islam, S.C. Mukhopadhay and N.K. Suryadevara, "Smart Sensors and Internet of Things: A Postgraduate Paper", IEEE Sensors Journal, Vol. 17, No. 3, Feb. 1, 2017.
  3. H. Chen, Y. Choi and P. B. Chou, "An Architecture for Programming and Managing Sensor and Actuator Networks in Enterprise Environment", Workshop on Building Software for Sensor Networks, 2006.
  4. L. Lamont, M. Toulgoat, M. Deziel, G. Patterson, "Tiered wireless sensor network architecture for military surveillance applications" International Conference on Sensor Technologies and Applications, pp. 288-94, 2011.
  5. Ojha T, Misra S, Raghuwanshi, "N S. Sensing-cloud: Leveraging the benefits for agricultural applications", Computers and Electronics in Agriculture, Vol. 135, pp. 66-84, 2017.
  6. F. Bordoni, A. D'Amico, "Noise in sensors", Sensors and Actuators A: Physical, Vol. 21, pp. 17-24, 1990. https://doi.org/10.1016/0924-4247(90)85003-M
  7. P. Maijala, Z. Shuyang, T. Heittola, T. Virtanen, "Environmental noise monitoring using source classification in sensors", Applied Acoustics, pp. 258-267, 2018
  8. D. Kim et al., "When Thermal Control Meets Sensor Noise: Analysis of Noise-induced Temperature Error", IEEE, 2015.
  9. J. Wilson, "Sensor Technology Handbook", Elsevier, 2005
  10. Technical article, "Understanding Sensor Resolution Specifications and Performance", TechNote, Lion Precision, Sept., 2014.
  11. B. Basnet et al., "An Smart Greenhouse Automation System Applying Moving Average Algorithm", KIEE, Vol. 65, No. 10, pp. 1755-1760, 2016.
  12. M. Aamir and M. F. Saleem, "Analysis of Noise Reduction Techniques in Embedded Systems", National Conference on Emerging Technologies, 2004.
  13. F. Reverter, "The Art of Directly Interfacing Sensors to Micro controllers", J. Low Power Electron. Appl., pp. 265-281, 2012.
  14. A. V. Oppenheim, E. Weinstein and K. C. Zangi, "Single-Sensor Active Noise Cancellation", IEEE Transactions on speech and audio processing, Vol. 2, No. 2, 1994.
  15. K. C. Zangi, "A New Two-Sensor Active Noise Cancellation Algorithm", IEEE, 1993.
  16. V. Y. Mendeleyev and A. V. Kourilovitch, "Optical sensor for reducing influence of intensity fluctuations on output stability", Optical Engineering 53(2), 027106, Feb., 2014. https://doi.org/10.1117/1.OE.53.2.027106
  17. K. H. Eom et al., "Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems", Sensors, 2011.
  18. P. H.G. Mani, I. Khan, and KVSVN Raju, "Sensors and Actuators Integration in Embedded Systems", ACEEE Int. J. on Network Security, Vol. 2, No. 2, Apr 2011.
  19. S. A. Haque, M. Rahman and S. M. Aziz, "Sensor Anomaly Detection in Wireless Sensor Networks for Healthcare", Sensors, 2015.
  20. S. Y. Lim and Y.H. Choi, "Malicious Node Detection Using a Dual Threshold in Wireless Networks", J. Sens. Actuator Netw., pp. 70-84, 2013.
  21. S. Chen, R. Lu and J. Zhang, "An Efficient Fog-Assisted Unstable Sensor Detection Scheme with Privacy Preserved", arXiv:1711.10190v1 [cs.CR] 28 Nov 2017.
  22. M. M. Rahman et al., "A False Alarm Reduction Method for a Gas Sensor Based Electronic Nose", Sensors, 2017.
  23. M. Athanassiades, O. Smith, "Theory and design of high-order bang-bang control systems", IRE Transactions on Automatic Control, Vol. 6, Issue: 2, May, 1961.
  24. M.B. Rhudy, R.A. Salguero and K. Holappa, "A Kalman Filtering Tutorial For Undergraduate Students", International Journal of Computer Science & Engineering survery (IJCSEE), Vol. 8, No. 1, Feb. 2017.
  25. Y. Zhao, "Fault Detection and Classification and protection in Solar Photovoltaic Arrays", Ph.D Thesis, Northeastern University, pp. 73-77, Aug., 2015.