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Kalman Filter-Based Fault Detection Scheme for Antenna Azimuth Position Control System

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Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 829))

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Abstract

Fault detection (FD) is an essential requirement of any engineering process to ensure its safety and reliability. DC motor-based servo system is an integral part of the position control system (PCS) in antenna-based communication systems. In this paper, the sensor FD problem in a linear model of DC motor subjected to Gaussian noise is addressed for reliable operation of the PCS. For this purpose, a model-based Kalman filter approach is adopted to design the FD system because of the Kalman filter’s ability to generate unbiased estimates of the system output in sense of least mean square estimation error. In this approach, residual is generated utilizing Kalman filter and residual is evaluated and compared with the threshold to indicate the occurrence of the fault. In the end, a simulation example is provided to validate the effectiveness of the proposed Kalman filter-based FD approach.

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References

  1. Salimi, A., Batmani, Y., Bevrani, H.: Model-based fault detection in DC microgrids, In: 2019 Smart Grid Conference, pp. 1–6. IEEE, Iran (2019)

    Google Scholar 

  2. Gertler, J.J.: Fault Detection & Diagnosis in Engineering Systems. CRC Press, USA (2017)

    Book  Google Scholar 

  3. Ahmad, M., Mohd-Mokhtar, R.: H-indexed fault sensitive filter design for linear discrete-time uncertain dc motor system. Interciencia J. 45(10), 60–74 (2020)

    Google Scholar 

  4. Nise, N.S.: Control System Engineering. John Wiley & Sons, USA (2015)

    MATH  Google Scholar 

  5. Ding, S.X.: Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. Springer, London (2013)

    Book  Google Scholar 

  6. Chen, J., Patton, R.J.: Robust Model-Based Fault Diagnosis For Dynamic Systems. Springer, Boston (2012)

    MATH  Google Scholar 

  7. Ding, S.X.: Data-Driven Design of Fault Diagnosis and Fault-Tolerant Control Systems. Springer, London (2014)

    Book  Google Scholar 

  8. Yin, S., et al.: A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process. J. Process Control 22(9), 1567–1581 (2012)

    Article  Google Scholar 

  9. Isermann, R.: Fault-Diagnosis Systems. Springer, Berlin (2006)

    Book  Google Scholar 

  10. Na, Y., Ahmad, M.: A fault detection scheme for switched systems with noise under asynchronous switching. In: 2019 9th International Conference on Information Science and Technology (ICIST), pp. 258–262, IEEE, China (2019)

    Google Scholar 

  11. Doraiswami, R., Cheded, L.: A unified approach to detection and isolation of parametric faults using a Kalman filter residual-based approach. J. Franklin Inst. 350(5), 938–965 (2013)

    Article  MathSciNet  Google Scholar 

  12. Jokic, I., Zecevic, Z., Krstajic, B.: State-of-charge estimation of lithium-ion batteries using extended Kalman filter and unscented Kalman filter, In: 23rd International Conference on IT, pp. 1–4, IEEE, Montenegro (2018)

    Google Scholar 

  13. Tripathi, R.P., Ghosh, S., Chandle, J.O.: Tracking of an object using optimal adaptive Kalman filter. In: ICETECH, pp. 1128–1131. IEEE, India (2016)

    Google Scholar 

  14. Temelkovski, J., Achkoski, B.: Modeling and simulation of antenna azimuth position control system. Int. J. Multidiscip. Curr. Res. 2, 254–257 (2014)

    Google Scholar 

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Acknowledgment

This research is partially supported by the Fundamental Research Grant Scheme: FRGS/1/2019/TK04/USM/02/12.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300, NibongTebal, Pulau Pinang, Malaysia

    Masood Ahmad & Rosmiwati Mohd-Mokhtar

Authors
  1. Masood Ahmad
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  2. Rosmiwati Mohd-Mokhtar
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Corresponding author

Correspondence to Rosmiwati Mohd-Mokhtar .

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Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Nor Muzlifah Mahyuddin

  2. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Nor Rizuan Mat Noor

  3. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Harsa Amylia Mat Sakim

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Ahmad, M., Mohd-Mokhtar, R. (2022). Kalman Filter-Based Fault Detection Scheme for Antenna Azimuth Position Control System. In: Mahyuddin, N.M., Mat Noor, N.R., Mat Sakim, H.A. (eds) Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications. Lecture Notes in Electrical Engineering, vol 829. Springer, Singapore. https://doi.org/10.1007/978-981-16-8129-5_33

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