Simulation analysis of extended Kalman filter applied for estimating position and speed of a brushless DC motor

• Autorzy: Chojowski M.

Identyfikatory

DOI

10.2478/pead-2018-0008

• Języki publikacji: EN

Abstrakty

EN

The purpose of this paper was to present a method for the estimation of the rotor speed and position of brushless DC (BLDC) motor. The BLDC motor state equations were developed, and the model was discretised. Extended Kalman filter has been designed to observe specific states from the state vector, needed for the sensorless control (rotor position) and to determine the speed, which may be useful to use as a feedback for the controller. A test was carried out to determine the noise covariance matrices in a simulation manner.

Słowa kluczowe

EN

extended Kalman filter; brushless DC motor; covariance matrix; sensorless control; BLDC

• Wydawca: De Gruyter
• Czasopismo: Power Electronics and Drives
• Rocznik: 2018
• Tom: Vol. 3 (38), No. 1
• Strony: 145--155
• Opis fizyczny: Bibliogr. 14 poz., rys., tab.

Twórcy

autor

Chojowski M.

• AGH University of Science and Technology, Al. Adama Mickiewicza 30, 30-059 Kraków, Poland

Bibliografia

• Aishwarya, V. and Jayanand, B. (2016). Estimation and control of sensorless brushless DC motor drive using extended Kalman filter. In: IEEE International Conference on Circuit, Power and Computing Technologies (ICCPCT), India.
• Auger, F., Hilairet, M., Guerrero, J. M., Monmasson, E., Orlowska-Kowalska, T. and Katsura, S. (2013). Industry Applications of the Kalman Filter: A Review. IEEE Transactions on Industrial Electronics, 60, pp. 5458-5471.
• Dhaouadi, R., Mohan, N. and Norum, L. (1991). Design and Implementation of an Extended Kalman Filter for the State Estimation of a Permanent Magnet Synchronous Motor. IEEE Transactions on Power Electronics, 6(3), pp. 491-497.
• Eissa, M. A., Ahmed, M. S., Darwish, R. R. and Bassiuny, A. M. (2015). Improved fuzzy Luenberger observer-based fault detection for BLDC motor. In: 2015 Tenth International Conference on Computer Engineering & Systems (ICCES), Cairo, IEEE, pp. 167-174. doi: 10.1109/ICCES.2015.7393039.
• El Mekki, A. and Ben Saad, K. (2016). A BLDC fault diagnosis approach based on a super-twisting sliding mode observer. In: 2016 4th International Conference on Control Engineering & Information Technology (CEIT), Hammamet, IEEE, pp. 1-5. doi: 10.1109/CEIT.2016.7929039.
• Jethwani, A., Aseri, D., Singh, T. S. and Jain, A. K. (2016). A simpler approach to the modelling of permanent magnet brushless DC machine in MATLAB environment. In: 6th IEEE International Conference on Power Systems (ICPS), India.
• Lenine, D., Rami Reddy, B. and Vijay Kumar, S. (2007). Estimation of speed and rotor position of BLDC motor using extended Kalman filter. In: IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), Chennai, Tamil Nadu, India, 20-22 December 2007, Dr. M.G.R. University, pp. 433-440.
• Ryba, Ł., Voda A., Besancon G. (2014). An LQG/ LTR Approach Towards Piezoactuator Vibration Reduction With Observer-Based Hysteresis Compensation. IFAC Proceedings Volumes, 47(3), pp. 5623-5628.
• Matlab Simulink. (2018). Mathworks: Permanent Magnet Synchronous Machine. Available at: https://www.mathworks.com [Accessed Jan. 2018].
• Simon, D. (2006). Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. USA: Wiley-Interscience. [ISBN: 978-0-471-70858-2].
• Šlapák, V., Kyslan, K., Fedák, V. and Ďurovský, F. (2016). Finite Control Set Model Predictive Speed Control of a DC Motor. Mathematical Problems in Engineering, 2016, p. 10 (9571972). doi: 10.1155/2016/9571972.
• Terzic, B. and Jadric, M. (2001). Design and Implementation of the Extended Kalman Filter for the Speed and Rotor Position Estimation of Brushless DC Motor. IEEE Transactions on Industrial Electronics, 48(6), pp. 1065-1073.
• Vinida, K. and Chacko, M. (2016). An optimized H infinity strategy for robust control of sensorless BLDC propulsion motor in submarines for improved maneuverability. In: 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Trivandrum, IEE, pp. 1-6.
• Zabalawi, S. A. and Nasiri, A. (2007). State space modeling and simulation of sensorless control of brushless DC motors using instantaneous rotor position tracking. In: IEEE Vehicle Power and Propulsion Conference (VPPC), Arlington, TX, USA.