Isolation and Identification of Periodic Disturbances in BLDC Motors

https://doi.org/10.58571/CNCA.AMCA.2023.032

Resumen: A high-gain linear observer is proposed for online identification and reconstruction of a periodic disturbance. It is assumed that the frequency of the periodic disturbance is known, but its amplitude and phase are unknown. This is not a stringent assumption since such supposition can be easily characterized for disturbances like cogging torque, or bearing defects, both well-known problems in the control of electric machines. The observer design is based on the internal model principle in combination with a high-gain observer. Numerical results are included to validate the estimation of the periodic disturbance even when another disturbance of a different frequency is added. The estimated disturbance can be used to design a controller for reducing the disturbance effect. Alternatively, the estimated disturbance can be used for fault detection like in the case of gears and bearing faults, or simply to characterize the cogging torque of a particular machine.

¿Cómo citar?

De La Guerra, Alejandra; Coronado-Andrade, Axel; Gutierrez-Giles, Alejandro. Isolation and Identification of Periodic Disturbances in BLDC Motors. Memorias del Congreso Nacional de Control Automático, pp. 121-126, 2023. https://doi.org/10.58571/CNCA.AMCA.2023.032

Palabras clave

Modelado e Identificación de Sistemas; Sistemas Electromecánicos; Control de Sistemas No Lineales

• Alonge, F., Cirrincione, M., D’Ippolito, F., Pucci, M., and Sferlazza, A. (2017). Active disturbance rejection control of linear induction motor. IEEE Transactions on Industry Applications, 53(5), 4460-4471.
• Alsogkier, I. and Bohn, C. (2012). Identification and control of periodic disturbances. In 2012 20th Mediterranean Conference on Control & Automation (MED), 265-271. IEEE.
• Alsogkier, I. and Bohn, C. (2017). Rejection and compensation of periodic disturbance in control systems. The International Journal of Engineering and Information Technology.
• Beltran-Carbajal, F., Tapia-Olvera, R., Valderrabano-Gonzalez, A., Yanez-Badillo, H., Rosas-Caro, J., and Mayo-Maldonado, J. (2021). Closed-loop online harmonic vibration estimation in dc electric motor systems. Applied Mathematical Modelling, 94, 460-481.
• Bourdon, A., André, H., and Rémond, D. (2014). Introducing angularly periodic disturbances in Dynamic models of rotating systems under non-stationary conditions. Mechanical systems and signal processing, 44(1-2), 60-71.
• Chiasson, J. (2005). Modeling and high performance control of electric machines. John Wiley & Sons.
• Chu, H., Gao, B., Gu, W., and Chen, H. (2016). Lowspeed control for permanent-magnet dc torque motor using observer-based nonlinear triple-step controller. IEEE Transactions on Industrial Electronics, 64(4), 3286-3296.
• Cort´es-Romero, J., Ramos, G.A., and Coral-Enriquez, H. (2014). Generalized proportional integral control for periodic signals under active disturbance rejection approach. ISA transactions, 53(6), 1901-1909.
• de la Guerra, A. and Alvarez-Icaza, L. (2020). Robust control of the brushless dc motor with variable torque load for automotive applications. Electric Power Components and Systems, 48(1-2), 117-127.
• de la Guerra, A., Alvarez-Icaza, L., and Torres, L. (2018). Brushless dc motor control with unknown and variable torque load. IFAC-PapersOnLine, 51(13), 644-649.
• Deenadayalan, A. and Ilango, G.S. (2011). Modified sliding mode observer for position and speed estimations in brushless dc motor. In Proceedings of the 2011 Annual IEEE India Conference, 1-4. IEEE.
• Fico, V.M., Rodr´ıguez V´azquez, A.L., Mart´ın Prats, M. ´, and Bernelli-Zazzera, F. (2019). Failure detection by signal similarity measurement of brushless dc motors. Energies, 12(7), 1364.
• Khalil, H.K. (2002). Nonlinear systems; 3rd ed. Prentice-Hall, Upper Saddle River, NJ. URLhttps://cds.cern.ch/record/1173048. The book can be consulted by contacting: PH-AID: Wallet, Lionel.
• Niewiara, , Tarczewski, T., and Grzesiak, L.M. (2020). Application of extended kalman filter for estimation of periodic disturbance and velocity ripple reduction in pmsm drive. Bulletin of the Polish Academy of Sciences. Technical Sciences, 68(5).
• Ramírez, H.S., Monta˜nez, F.G., Romero, J.C., and Luviano-Juárez, A. (2013). State observers for active disturbance rejection in induction motor control. AC Electric Motors Control: Advanced Design Techniques and Applications, 78-104.
• Reyna, M.A., Gómez-Espinosa, A., and Rodríguez, C.A. (2018). Adaptive fourier series speed controller for permanent magnet synchronous motor and brushless dc motor. In Journal of Physics: Conference Series, volume 1074, 012012. IOP Publishing.
• Ruderman, M., Ruderman, A., and Bertram, T. (2012). Observer-based compensation of additive periodic torque disturbances in permanent magnet motors. IEEE Transactions on Industrial Informatics, 9(2), 1130-1138.
• Rugh Wilson, J. (1993). Linear systems theory. 2. Shao, Y., Yang, R., Guo, J., and Fu, Y. (2015). Sliding mode speed control for brushless dc motor based on sliding mode torque observer. In Proceedings of the 2015 IEEE International Conference on Information and Automation, 2466-2470. IEEE.
• Yilmaz, C.T. and Basturk, H.I. (2019). Output feedback control for unknown lti systems driven by unknown periodic disturbances. Automatica, 99, 112-119.
• Zarei, J., Tajeddini, M.A., and Karimi, H.R. (2014). Vibration analysis for bearing fault detection and classification using an intelligent filter. Mechatronics, 24(2), 151-157.
• Zhu, X. and Li, W. (2019). Takagi–sugeno fuzzy model based shaft torque estimation for integrated motor–transmission system. ISA transactions, 93, 14-22.