DOI QR코드

DOI QR Code

Sensorless speed control of permanent magnet synchronous motor using square-root extended kalman filter

제곱근 확장 칼만 필터에 의한 영구자석 동기전동기의 센서리스 속도제어

  • Moon, Cheol (Department of Electrical and Computer Engineering Pusan National University) ;
  • Kwon, Young-Ahn (Department of Electrical and Computer Engineering Pusan National University)
  • Received : 2015.11.11
  • Accepted : 2016.02.24
  • Published : 2016.03.31

Abstract

This study investigates the design, analysis, and implementation of the square-root extended Kalman filter by using an algorithm derived by combining the Potter or Carlson algorithm with the modified Gram-Schmidt algorithm, for sensorless speed control of a permanent-magnet synchronous motor. The sensitivity of the Kalman filter to round-off errors is a well-known problem. A possible way to address this limitation is by combining the square-root concept and Kalman filter that can improve the numerical performance and solve instability-related problems such as divergence. This paper presents the design and analysis of the implementation of such a square-root extended Kalman filter. To demonstrate the performance of the proposed filter, experimental results under several operating conditions, such as high and low speeds, reversal rotation, detuned parameters and load test, have been analyzed. Further, code sizes and operation times have been compared. Experimental results establish the performance of the proposed square-root extended Kalman filter-based estimation technique for sensorless speed control of a permanent-magnet synchronous motor.

본 논문은 수정된 Gram-Schmidt와 결합한 Potter 또는 Carlson 알고리즘을 가지는 제곱근 확장 칼만 필터에 의한 영구자석 동기전동기의 센서리스 속도 제어에 관한 연구이다. 일반적으로 반올림 오차에 기인하는 칼만 필터의 민감도는 잘 알려진 문제이다. 제곱근 개념과 칼만 필터의 결합은 수치적 성능을 향상할 수 있고 발산과 같은 불안전한 문제를 풀 수 있다. 본 논문에서는 제곱근 확장 칼만 필터의 구현을 위한 설계와 분석을 수행하였다. 설계된 제곱근 확장 칼만 필터의 추정 성능을 입증하기 위해, 고속, 저속, 역 회전, 파라미터 변동, 부하 변동 실험 등 여러 운전 조건 아래에서 실험 결과들을 분석하였다. 또한, 프로그램 코드 크기 및 연산 시간을 비교하였다. 실험적 결과들은 제곱근 확장 칼만 필터에 의한 영구자석 동기전동기의 센서리스 속도 제어가 양호함을 보인다.

Keywords

References

  1. K. Rajashekara, A. Kawamura, and K. Matsuse, Sensorless control of AC motor drives, IEEE Press, 1996.
  2. J. Holtz, "State of the art of controlled AC drive without speed sensor," Proceedings of 1995 International Conference on Power Electronics and Drive Systems, pp. 1-6, 1995.
  3. I. Boldea, "Control issues in adjustable speed drives," IEEE Industrial Electronics Magazine, vol. 2, no. 3, pp. 32-50, 2008. https://doi.org/10.1109/MIE.2008.928605
  4. R. E. Kalman, "A new approach to linear filtering and prediction problems," Transactions of the ASME-Journal of Basic Engineering, vol. 82, no. 1, pp. 35-45, Mar. 1960. https://doi.org/10.1115/1.3662552
  5. S. Bolognani, R. Oboe, and M. Zigliotto, "Sensorless full-digital PMSM drive with EKF estimation of speed and rotor position," IEEE Transactions on Industrial Electronics, vol. 46, no. 1, pp. 184-191, 1999.
  6. F. Alonge, F. D.'Ippolito, and A. Sferlazza, "Sensorless control of induction-motor drive based on robust Kalman filter and adaptive speed estimation," IEEE Transactions on Industrial Electronics, vol. 61, no. 3, pp. 1444-1453, 2014. https://doi.org/10.1109/TIE.2013.2257142
  7. M. Barut, R. Demir, E. Zerdali, and R. Inan, "Real-time implementation of bi input-extended Kalman filter-based estimator for speed-sensorless control of induction motors,"IEEE Transactions on Industrial Electronics, vol. 59, no. 11, pp. 4197-4206, 2012. https://doi.org/10.1109/TIE.2011.2178209
  8. N. Salvatore, A. Caponio, F. Neri, S. Stasi, and G. Cascella, "Optimization of delayed-state Kalman-filter-based algorithm via differential evolution for sensorless control of induction motors," IEEE Transactions on Industrial Electronics, vol. 57, no. 1, pp. 385-394, 2010. https://doi.org/10.1109/TIE.2009.2033489
  9. J. S. Jang, B. G. Park, T. S. Kim, D. M. Lee, and D. S. Hyun, "Parallel reduced-order extended Kalman filter for PMSM sensorless drives," Proceedings of IECON'2008, pp. 1326-1331, 2008.
  10. M. Grewal and A. Andrews, Kalman Filtering: Theory and Practice Using MATLAB. Hoboken. NJ: Wiley-IEEE Press, 2008.
  11. J. Schmit, Analysis of Square-root Kalman Filter for Angle-Only Orbital Navigation and the Effects of Sensor Accuracy on State Observability, M.S Thesis, Utah State University, U.S.A, 2010.
  12. V. Smidl and Z. Peroutka, "Advantages of square-root extended Kalman filter for sensorless control of AC drives," IEEE Transaction on Industrial Electronics, vol. 59, no. 11, pp. 4189-4196, 2012. https://doi.org/10.1109/TIE.2011.2180273
  13. S. Jafarzadeh, C. Lascu, and M. S. Fadali, "Square root unscented Kalman filters for state estimation of induction motor drives," IEEE Transaction on Industry Applications, vol. 49, no. 1, pp. 92-99, 2013. https://doi.org/10.1109/TIA.2012.2229251