Control of a Dc Motor using Sensorless Observer Based Sliding Mode Control Method
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2018 by IJETT Journal|
|Year of Publication : 2018|
|Authors : Tayfun Abut
|DOI : 10.14445/22315381/IJETT-V66P212|
MLA Style: Tayfun Abut "Control of a Dc Motor using Sensorless Observer Based Sliding Mode Control Method" International Journal of Engineering Trends and Technology 66.2 (2018): 67-72.
APA Style:Tayfun Abut (2018). Control of a Dc Motor using Sensorless Observer Based Sliding Mode Control Method. International Journal of Engineering Trends and Technology, 66(2), 67-72.
Sensorless control methods are one of the control methods that continue to develop in recent years.In these control types, the target rotor is to obtain the speed and position information from the measured quantities such as voltage and current. There are several methods for sensorless control. These methods are usually affected by the dc motor`s parameter changes, uncertainties and disturbing factors, which leads to a reduction in the quality of the control. In this study, an observer-based sliding mode control method is proposed for position and speed-free control of a DC motor. Luenberger and Kalman filter observer methods were used as observers for control of DC motor. The saturation function is used for the cracking problem of the sliding mode control method. Both the process noise and the measurement noise were applied to control the DC motor system in conditions close to the actual ambient conditions. A second-order low-pass filter design has been designed to improve the performance of the controllers in the noise environment. As a result of these studies, the controller was designed and graphical results were obtained in order to be used in a real physical environment. The control methods applied according to the results of the simulation environment were compared and the results were examined.
 Zhenguo, L., Songfa, Z., Shenghai, Z., & Chunjiang, Z. Direct torque control of brushless DC motor consideringtorque ripple minimization. Transactions of China Electrotechnical Society, 29(1), 139-146,(2014).
 Schmidt, R. A., Lee, T., Winstein, C., Wulf, G., & Zelaznik, H. Motor Control and Learning, 6E. Human Kinetics, (2018).
 Blakemore, R. L., Sinanaj, I., Galli, S., Aybek, S., & Vuilleumier, P. Aversive stimuli exacerbate defensive motor behavior in motor conversion disorder. Neuropsychologia, 93, 229-241, (2016).
 Zhang, Z., Zhang, X., Chen, W., Rasim, Y., Salman, W., Pan, H., ... & Wang, C. A high-efficiency energy regenerative shock absorber using supercapacitors for renewable energy applications in range-extended electric vehicle. Applied Energy, 178, 177-188, (2016).
 Denton, Tom. Automobile electrical and electronic systems. Routledge, 2017.
 Oshaba, A. S., E. S. Ali, and SM Abd Elazim. "PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load." Neural Computing and Applications 28.2 (2017): 353-364.
 Ison, M., Vujaklija, I., Whitsell, B., Farina, D., & Artemiadis, P. High-density electromyography and motor skill learning for robust long-term control of a 7-DoF robot arm. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(4), 424-433, (2016).
 Baber, D. L., Leimbach, R. L., & Ulrich, D. J. U.S. Patent No. 9,554,794. Washington, DC: U.S. Patent and Trademark Office, (2017).
 Praveen, R. P., Ravichandran, M. H., Achari, V. S., Raj, V. J., Madhu, G., & Bindu, G. R. A novel slotless Halbach-array permanent-magnet brushless dc motor for spacecraft applications. Industrial Electronics, IEEE Transactions on, 59(9), 3553-3560,(2012).
 T. Abut, “Modeling and Optimal Control of a DC Motor,” Int. J. Eng. Trends Technol., vol. 32, no. 3, pp. 146–150, 2016.
 Mondal, S., Majumder, A., Chowdhury, D., & Chattopadhyay, M. An efficient power delivering scheme for the sensorless drive of Brushless DC motor. Microsystem Technologies, 1-8, (2018).
 Gan, M. G., Zhang, M., Zheng, C. Y., & Chen, J. An adaptive sliding mode observer over wide speed range for sensorless control of a brushless DC motor. Control Engineering Practice, 77, 52-62, (2018).
 Cui, C., Liu, G., Wang, K., & Song, X. Sensorless drive for high-speed brushless DC motor based on the virtual neutral voltage. IEEE Transactions on Power Electronics, 30(6), 3275-3285, (2015).
 Choi, J., Nam, K., Bobtsov, A. A., Pyrkin, A., & Ortega, R. Robust adaptive sensorless control for permanent-magnet synchronous motors. IEEE Transactions on Power Electronics, 32(5), 3989-3997, (2017).
 Chen, W., Liu, Z., Cao, Y., Li, X., Shi, T., & Xia, C. A Position Sensorless Control Strategy for BLDCM Based on Flux-Linkage Function. IEEE Transactions on Industrial Electronics, (2018).
 Bazylev, D., Vukosavic, S., Bobtsov, A., Pyrkin, A., Stankovic, A., & Ortega, R. Sensorless control of PM synchronous motors with a robust nonlinear observer. In 2018 IEEE Industrial Cyber-Physical Systems (ICPS) (pp. 304-309). IEEE, (2018, May).
 Fan, Y., Zhang, L., Cheng, M., & Chau, K. T. Sensorless SVPWM-FADTC of a new flux-modulated permanent-magnet wheel motor based on a wide-speed sliding mode observer. IEEE Transactions on Industrial Electronics, 62(5), 3143-3151, (2015).
 Dehghan-Azad, E., Gadoue, S., Atkinson, D., Slater, H., Barrass, P., & Blaabjerg, F. Sensorless control of IM based on stator-voltage MRAS for Limp-home EV applications. IEEE Transactions on Power Electronics, 33(3), 1911-1921, (2018).
 Hasan, SM Nayeem, and Iqbal Husain. "A Luenberger–Sliding mode observer for online parameter estimation and adaptation in high-performance induction motor drives." IEEE Transactions on industry applications 45.2 (2009): 772-781.
 Kaewpoo, N., Ohyama, K., Nakazawa, Y., Fujii, H., Uehara, H., & Hyakutake, Y. Simulation of SRM Sensorless Control System for Electric Vehicle. In 2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) (pp. 1-4). IEEE, (2018, July).
 C. Mitsantisuk, K. Ohishi, S. Urushihara, and S. Katsura, “Kalman filterbased disturbance observer and its application to sensorless force control,” Adv. Robot., vol. 25, no. 3, pp. 335–353, Feb. 2011.
 F. Alonge, F. D’Ippolito, and A. Sferlazza, "Sensorless control of induction motor drive based on robust Kalman filter and adaptive speed estimation," IEEE Trans. Ind. Electron, vol. 61, no. 3, pp. 1444–1453, 2014.
 Itk?s, U., Control systems of variable structure, Wiley, New York, 1976.
 Utk?n, V.I., Variable structure systems with sliding modes, IEEE transactions on automatic control, 22, 212-222, 1977,
 V. I. Utkin, “Sliding modes and their application in variable structure systems”, MIR, Moscow, 1974.
 Palm, R., Sliding mode fuzzy control, Proceedings of the IEEE international conference on fuzzy systems, San Diego, 519-526, 1992.
 Park, J.H., Lee, Y.J., Robust visual servoing for motion control of the ball on a plate, Mechatronics, 13 (2003), 723-738.
 Di Gennaro, Stefano, Jorge Rivera Domínguez, and Marco Antonio Meza. "Sensorless high order sliding mode control of induction motors with core loss." IEEE Transactions on Industrial Electronics 61.6 (2014): 2678-2689.
 Zhao, L., Huang, J., Liu, H., Li, B., & Kong, W. Second-order sliding-mode observer with online parameter identification for sensorless induction motor drives. IEEE Transactions on Industrial Electronics, 61(10), 5280-5289, (2014).
 Wang, J., Li, S., Yang, J., Wu, B., & Li, Q. Extended state observer-based sliding mode control for PWM-based DC-DC buck power converter systems with mismatched disturbances. IET Control Theory & Applications, 9(4), 579-586, (2015).
 Mohammed Golam Sarwer, Md. Abdur Rafiq and B.C. Ghosh," Sliding Mode Speed Controller of a D.C Motor Drive", Journal of Electrical Engineering, The Institution of Engineers, Bangladesh, Vol. EE 31, No. I & II, December 2004.
 Liang, D., Li, J., Qu, R., & Kong, W. Adaptive second-order sliding-mode observer for PMSM sensorless control considering VSI nonlinearity. IEEE Transactions on Power Electronics, 33(10), 8994-9004, (2018).
 Dong, C. S., Tran, C. D., Ho, S. D., Brandstetter, P., & Kuchar, M. Robust sliding mode observer application in vector control of induction motor. In 2018 ELEKTRO (pp. 1-5). IEEE, (2018, May).
 Simon, D.: Optimal State Estimation: Kalman, H-infinity and Nonlinear Approaches. Wiley, New York (2006).
 Yang, B., Liu, M., Kim, H., & Cui, X. Luenberger-sliding mode observer based fuzzy double loop integral sliding mode controller for the electronic throttle valve. Journal of Process Control, 61, 36-46, (2018).
 You, J., Wu, W., & Wang, Y. An Adaptive Luenberger Observer for Speed-Sensorless Estimation of Induction Machines. In 2018 Annual American Control Conference (ACC) (pp. 307-312). IEEE, (2018, June).
 Zhang, Y., Zhao, Z., Lu, T., Yuan, L., Xu, W., & Zhu, J. (2009, September). A comparative study of Luenberger observer, sliding mode observer and extended Kalman filter for sensorless vector control of induction motor drives. In Energy Conversion Congress and Exposition, 2009. ECCE 2009. IEEE (pp. 2466-2473). IEEE.
 Yahia, K., Zouzou, S. E., Benchabane, F., & Taibi, D. Comparative study of an adaptive Luenberger observer and extended Kalman filter for a sensorless direct vector control of induction motor. Acta Electrotehnica, 50(2), 99-107, (2009).
 Kalman, R. E., “Contributions to the Theory of Optimal Control,” Bol. Soc Mat. Mex., 5 pp. 102–19, (1960).
 Mohinder S G, Angus P A. "Kalman Filtering: Theory and practice". 2nded. New York: John Wiley and Sons, 2001, pp. 133-148.
 C. Yong Yi, A. Shimada, and N. Fujii: Kalman filter based disturbance observer and an observation of the use of disturbance estimate, Proc. 51st Joint Automatic Control Conference, pp.1226–1231, 2008 (in Japanese).
 Abut, T. "Dynamic Model And Optimal Control Of A Snake Robot: TAROBOT–1." International Journal of Scientific & Technology Research (Impact Factor: 0.68). 11/2015; 4(11):240-248.
Sliding Mode Control Method, Luenberger observer, Kalman Filter, Sensorless, DC motor