Position Control Improvement of Permanent Magnet Motor Using Model Predictive Control

Authors

Electrical Engineering Department, Tafresh University, Tafresh, Iran

Abstract

Fast and accurate transient response is the main requirement in electric machine position control. Conventional cascade control structure has sluggish response due to the limitation of inner control loop bandwidth. In this paper, in order to decrease the Permanent Magnet Synchronous Motor (PMSM) transient response time it can be used reference model using feed-forward signals. In this structure, feed-forward signals generated by simplified model of permanent magnet synchronous motor. In this paper, feed-forward signals generated are emplyed in model predictive control; which are combined with conventional cascade control structure. Using this approach, a fast transient response and satisfactory tracking ability will be guaranteed. The proposed method is compared with the model reference method and conventional cascade structure. Simulation results showed a good performance of proposed method related to both methods. Verification of simulation results were carried out by experimental results

Keywords


1.     Tami, R., Boutat, D., Zheng, G., Kratz, F. and El Gouri, R., "Rotor speed, load torque and parameters estimations of a permanent magnet synchronous motor using extended observer forms", IET Control Theory & Applications,  Vol. 11, No. 9, (2017), 1485-1492.
2.     Kadjoudj, M., Benbouzid, M.E.H., Ghennai, C. and Diallo, D., "A robust hybrid current control for permanent-magnet synchronous motor drive", IEEE Transactions on Energy Conversion,  Vol. 19, No. 1, (2004), 109-115.
3.     Pilla, R., Tummala, A. and Chintala, M., "Tuning of extended kalman filter using self-adaptive differential evolution algorithm for sensorless permanent magnet synchronous motor drive", International Journal of Engineering-Transactions B: Applications,  Vol. 29, No. 11, (2016), 1565-1573.
4.     Pukpinyo, C. and Assawinchaichote, W., "Ts fuzzy based h-infinity speed controller design for uncertain surface-mounted permanent-magnet synchronous motor", in Computer Science and Engineering Conference (ICSEC), 2016 International, IEEE., (2016), 1-6.
5.     Suman, S.K., Gautam, M.K., Srivastava, R. and Giri, V.K., "Novel approach of speed control of pmsm drive using neural network controller", in Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on, IEEE., (2016), 2780-2783.
6.     Hsu, C.-J. and Lai, Y.-S., "Novel on-line optimal bandwidth search and auto tuning techniques for servo motor drives", in Energy Conversion Congress and Exposition (ECCE), 2016 IEEE, IEEE., (2016), 1-8.
7.     Choi, S.-H., Ko, J.-S., Kim, I.-D., Park, J.-S. and Hong, S.-C., "Precise position control using a pmsm with a disturbance observer containing a system parameter compensator", IEE Proceedings-Electric Power Applications,  Vol. 152, No. 6, (2005), 1573-1577.
8.     Shyu, K.-K., Lai, C.-K., Tsai, Y.-W. and Yang, D.-I., "A newly robust controller design for the position control of permanent-magnet synchronous motor", IEEE Transactions on Industrial Electronics,  Vol. 49, No. 3, (2002), 558-565.
9.     Yu, H., Liu, X., Yu, J. and Song, Q., "Position tracking control of pmsm based on state error pch and mtpa principle", in Robotics, Automation and Mechatronics (RAM), 2011 IEEE Conference on, IEEE., (2011), 113-118.
10.   Kumar, V., Gaur, P. and Mittal, A., "Ann based self tuned pid like adaptive controller design for high performance pmsm position control", Expert Systems with Applications,  Vol. 41, No. 17, (2014), 7995-8002.
11.   Jon, R., Wang, Z., Luo, C. and Jong, M., "Adaptive robust speed control based on recurrent elman neural network for sensorless pmsm servo drives", Neurocomputing,  Vol. 227, (2017), 131-141.
12.   Lin, C.H., "Adaptive recurrent chebyshev neural network control for pm synchronous motor servo‐drive electric scooter with v‐belt continuously variable transmission", International Journal of Adaptive Control and Signal Processing,  Vol. 29, No. 7, (2015), 805-834.
13.   Cortés, P., Kazmierkowski, M.P., Kennel, R., Quevedo, D.E. and Rodriguez, J.R., "Predictive control in power electronics and drives", IEEE Trans. Industrial Electronics,  Vol. 55, No. 12, (2008), 4312-4324.
14.   Clarke, D.W., Mohtadi, C. and Tuffs, P., "Generalized predictive control—part i. The basic algorithm", Automatica,  Vol. 23, No. 2, (1987), 137-148.
15.   Bolognani, S., Bolognani, S., Peretti, L. and Zigliotto, M., "Design and implementation of model predictive control for electrical motor drives", IEEE Transactions on Industrial Electronics,  Vol. 56, No. 6, (2009), 1925-1936.
16.   Abadi, A.G.R. and Hamidi, H., "Constrained model predictive control of low-power industrial gas turbine", International Journal of Engineering-Transactions B: Applications,  Vol. 30, No. 2, (2017), 207-214.
17.   Belda, K. and Vosmik, D., "Explicit generalized predictive algorithms for speed control of pmsm drives", in Industrial Electronics Society, IECON 2013-39th Annual Conference of the IEEE, IEEE., (2013), 2833-2838.
18.   Cimini, G., Fossi, V., Ippoliti, G., Mencarelli, S., Orlando, G. and Pirro, M., "Model predictive control solution for permanent magnet synchronous motors", in Industrial Electronics Society, IECON 2013-39th Annual Conference of the IEEE, IEEE., (2013), 5824-5829.
19.   Chai, S., Wang, L. and Rogers, E., "A cascade mpc control structure for a pmsm with speed ripple minimization", IEEE Transactions on Industrial Electronics,  Vol. 60, No. 8, (2013), 2978-2987.