TY - GEN
T1 - Model-free Predictive Torque Control of an Induction Machine Based on Parameter Estimation
AU - Young, Hector
AU - Nematshahi, Mahdi
AU - Sabzevari, Sanaz
AU - Heydari, Rasool
AU - Flores-Bahamonde, Freddy
AU - Gonzalez, Catalina
AU - Zhang, Yongchang
AU - Rodriguez, Jose
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The uncertainty or variation of the electric machine parameters in predictive torque control (PTC) has a noticeable impact on the controller's performance. This paper proposes a model-free PTC strategy based on the estimation of the prediction model parameters using input and output data of the controlled system, applied to an induction machine. This approach has the advantage of not requiring a detailed previous knowledge of the system, with a high robustness to mismatch in the inductance parameters of the machine. The stator resistance is identified as a critical parameter for PTC, therefore an adaptation mechanism based on support vector regression is proposed to increase the robustness of the system. Simulation tests are carried out to validate the effectiveness of the proposed strategy.
AB - The uncertainty or variation of the electric machine parameters in predictive torque control (PTC) has a noticeable impact on the controller's performance. This paper proposes a model-free PTC strategy based on the estimation of the prediction model parameters using input and output data of the controlled system, applied to an induction machine. This approach has the advantage of not requiring a detailed previous knowledge of the system, with a high robustness to mismatch in the inductance parameters of the machine. The stator resistance is identified as a critical parameter for PTC, therefore an adaptation mechanism based on support vector regression is proposed to increase the robustness of the system. Simulation tests are carried out to validate the effectiveness of the proposed strategy.
KW - induction motors
KW - Model-free predictive control
KW - parameter estimation
KW - support vector regression
UR - http://www.scopus.com/inward/record.url?scp=85125817030&partnerID=8YFLogxK
U2 - 10.1109/PRECEDE51386.2021.9681044
DO - 10.1109/PRECEDE51386.2021.9681044
M3 - Conference contribution
AN - SCOPUS:85125817030
T3 - 6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
SP - 725
EP - 731
BT - 6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
Y2 - 20 November 2021 through 22 November 2021
ER -