LMI-based Sensor-less Robust Predictive Control of Induction Motors by Torque Disturbance
محورهای موضوعی : پردازش چند رسانه ای، سیستمهای ارتباطی، سیستمهای هوشمند
Mehdi Safaeian
1
,
Seyyed Hamidreza Mousavi
2
*
,
Arash Shabani
3
1 - Assistant Professor, Department of Electrical Engineering, Hi.C., Islamic Azad University, Hidaj, Iran
2 - Assistant Professor, Department of Electrical Engineering, Z.C., Islamic Azad University, Zanjan, Iran
3 - Assistant Professor, Department of Electrical Engineering, Hi.C., Islamic Azad University, Hidaj, Iran
کلید واژه: Predictive control, Linear Matrix Inequalities, System, Uncertainty, Induction Motor,
چکیده مقاله :
|
In this paper, a new robust predictive control method for induction motors (IMs) is discussed. Linear matrix inequalities (LMIs) are employed, and feedback and observer matrices are designed in the presence of disturbances. To improve accuracy, a nonlinear motor model with parameter uncertainties and perturbations is used. With this nonlinear model, rotor speed is treated as one of the state variables and can be directly controlled using the proposed method. Additionally, uncertainty is incorporated to compensate for modeling errors or parameter mismatches. Finally, the effect of load torque is considered as a disturbance input to the system. Simulations and experimental results are presented at the end. |
|
In this paper, a new robust predictive control method for induction motors (IMs) is discussed. Linear matrix inequalities (LMIs) are employed, and feedback and observer matrices are designed in the presence of disturbances. To improve accuracy, a nonlinear motor model with parameter uncertainties and perturbations is used. With this nonlinear model, rotor speed is treated as one of the state variables and can be directly controlled using the proposed method. Additionally, uncertainty is incorporated to compensate for modeling errors or parameter mismatches. Finally, the effect of load torque is considered as a disturbance input to the system. Simulations and experimental results are presented at the end. |
[1] V. Ambrozic, G. S. Buja, and R. Menis, "Band-constrained technique for direct torque control of induction motor," IEEE Transactions on Industrial Electronics, vol. 51, no. 4, pp. 776–784, 2004.
[2] A. G. M. A. Aziz, H. Rez, and A. A. Z. Diab, "Robust sensorless model-predictive torque flux control for high-performance induction motor drives," Mathematics, vol. 9, no. 4, p. 403, 2021. doi: 10.3390/math9040403.
[3] S. A. Davari, D. A. Khaburi, F. Wang, and R. M. Kennel, "Using full order and reduced order observers for robust sensorless predictive torque control of induction motors," IEEE Transactions on Power Electronics, vol. 27, no. 7, pp. 3424–3433, 2012.
[4] P. Falugi and D. Q. Mayne, "Getting robustness against unstructured uncertainty: A tube-based MPC approach," IEEE Transactions on Automatic Control, vol. 59, no. 5, pp. 1295–1301, 2014.
[5] L. E. Ghaoul, E. Feron, V. Balakrishnan, and S. P. Boyd, Linear Matrix Inequalities in System and Control Theory, vol. 15, SIAM, 1994.
[6] D.-J. Kim and B. Kim, "Linear matrix inequality-based robust model predictive speed control for a permanent magnetic synchronous motor with a disturbance observer," Energies, vol. 17, no. 4, p. 869, 2024. doi: 10.3390/en17040869.
[7] M. V. Kothare, V. Balakrishnan, and M. Morari, "Robust constrained model predictive control using linear matrix inequalities," Automatica, vol. 32, no. 10, pp. 1361–1379, 1996.
[8] B. S. Lee and R. Krishnan, "Adaptive stator resistance compensator for high performance direct torque controlled induction motor drives," Proceedings of the IEEE Industry Applications Society Annual Meeting, St. Louis, MO, USA, 1998.
[9] S. B. Lee, T. G. Habetler, R. G. Harley, and D. J. Gritter, "An evaluation of model-based stator resistance estimation for induction motor stator winding temperature monitoring," Proceedings of the IEEE Industry Applications Conference, 2002.
[10] C. Løvaas, M. M. Seron, and G. C. Goodwin, "Robust output-feedback MPC with integral action," IEEE Transactions on Automatic Control, vol. 55, no. 7, pp. 1531–1543, 2010.
[11] D. Q. Mayne, M. M. Seron, and S. V. Raković, "Robust model predictive control of constrained linear systems with bounded disturbances," Automatica, vol. 41, no. 2, pp. 219–224, 2005.
[12] M. Nemec, D. Nedeljkovic, and V. Ambrozic, "Predictive torque control of induction machines using immediate flux control," IEEE Transactions on Industrial Electronics, vol. 54, no. 4, pp. 2009–2017, 2007.
[13] H. H. Nguyen and R. Findeisen, "LMI-based data-driven robust model predictive control," arXiv preprint arXiv:2303.04777, 2023. Available: https://arxiv.org/abs/2303.04777.
[14] N. D. Nguyen, N. N. Nam, C. Yoon, and Y. I. Lee, "Speed sensorless model predictive torque control of induction motors using a modified adaptive full-order observer," IEEE Transactions on Industrial Electronics, vol. 68, no. 4, pp. 3173–3183, 2021. doi: 10.1109/TIE.2020.2984567.
[15] S. E. Rezgui, S. Legrioui, A. Mehdi, and H. Benalla, "Robust IM control with MRAS-based speed and parameters estimation with ANN using exponential reaching law," Proceedings of the International Conference on Systems and Control, Metz, France, 2014.
[16] J. Rodríguez and P. Cortes, Predictive Control of Power Converters and Electrical Drives, Wiley-IEEE Press, 2012.
[17] A. Sivaprakasam and T. Manigandan, "An alternative scheme to reduce torque ripple and mechanical vibration in direct torque controlled permanent magnet synchronous motor," Journal of Vibration and Control, vol. 21, no. 5, pp. 855–871, 2015.