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Chinese Journal of Electrical Engineering 2023, 9(2): 27-37 https://doi.org/10.23919/CJEE.2023.000020
Regular Paper | Open Access | Issue | Published: 30 June 2023

An Improved Deadbeat Predictive Current Control of PMSM Drives Based on the Ultra-local Model

Show Author's Information Yongchang Zhang1( ),  Wenjia Shen2,  Haitao Yang2
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China
Keywords:
robustness, current control, Deadbeat control, PMSM drives
Cite this article:
Zhang Y, Shen W, Yang H. An Improved Deadbeat Predictive Current Control of PMSM Drives Based on the Ultra-local Model. Chinese Journal of Electrical Engineering, 2023, 9(2): 27-37. https://doi.org/10.23919/CJEE.2023.000020
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Abstract Full text About this article

Deadbeat predictive current control (DPCC) has been widely applied in permanent magnet synchronous motor (PMSM) drives due to its fast dynamic response and good steady-state performance. However, the control accuracy of DPCC is dependent on the machine parameters’ accuracy. In practical applications, the machine parameters may vary with working conditions due to temperature, saturation, skin effect, and so on. As a result, the performance of DPCC may degrade when there are parameter mismatches between the actual value and the one used in the controller. To solve the problem of parameter dependence for DPCC, this study proposes an improved model-free predictive current control method for PMSM drives. The accurate model of the PMSM is replaced by a first-order ultra-local model. This model is dynamically updated by online estimation of the gain of the input voltage and the other parts describing the system dynamics. After obtaining this ultra-local model from the information on the measured stator currents and applied stator voltages in past control periods, the reference voltage value can be calculated based on the principle of DPCC, which is subsequently synthesized by space vector modulation (SVM). This method is compared with conventional DPCC and field-oriented control (FOC), and its superiority is verified by the presented experimental results.


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About this article

An Improved Deadbeat Predictive Current Control of PMSM Drives Based on the Ultra-local Model

Show Author's information Yongchang Zhang1( ), Wenjia Shen2, Haitao Yang2
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China

Abstract

Deadbeat predictive current control (DPCC) has been widely applied in permanent magnet synchronous motor (PMSM) drives due to its fast dynamic response and good steady-state performance. However, the control accuracy of DPCC is dependent on the machine parameters’ accuracy. In practical applications, the machine parameters may vary with working conditions due to temperature, saturation, skin effect, and so on. As a result, the performance of DPCC may degrade when there are parameter mismatches between the actual value and the one used in the controller. To solve the problem of parameter dependence for DPCC, this study proposes an improved model-free predictive current control method for PMSM drives. The accurate model of the PMSM is replaced by a first-order ultra-local model. This model is dynamically updated by online estimation of the gain of the input voltage and the other parts describing the system dynamics. After obtaining this ultra-local model from the information on the measured stator currents and applied stator voltages in past control periods, the reference voltage value can be calculated based on the principle of DPCC, which is subsequently synthesized by space vector modulation (SVM). This method is compared with conventional DPCC and field-oriented control (FOC), and its superiority is verified by the presented experimental results.

Keywords: robustness, current control, Deadbeat control, PMSM drives

References(40)

[1]

Yongchang Zhang, Hao Jiang, Haitao Yang. Model predictive control of PMSM drives based on general discrete space vector modulation. IEEE Transactions on Energy Conversion, 2021, 36(2): 1300-1307.
DOI Google Scholar
[2]

D Casadei, F Profumo, G Serra, et al. FOC and DTC: Two viable schemes for induction motors torque control. IEEE Transactions on Power Electronics, 2002, 17(5): 779-787.
DOI Google Scholar
[3]

L Zhong, M F Rahman, W Y Hu, et al. Analysis of direct torque control in permanent magnet synchronous motor drives. IEEE Transactions on Power Electronics, 1997, 12(3): 528-536.
DOI Google Scholar
[4]

T Geyer, G Papafotiou, M Morari. Model predictive direct torque control—Part Ⅰ: Concept, algorithm, and analysis. IEEE Transactions on Industrial Electronics, 2009, 56(6): 1894-1905.
DOI Google Scholar
[5]

J Han. From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics, 2009, 56(3): 900-906.
DOI Google Scholar
[6]

Y Zhang, J Zhu. Direct torque control of permanent magnet synchronous motor with reduced torque ripple and commutation frequency. IEEE Transactions on Power Electronics, 2011, 26(1): 235-248.
DOI Google Scholar
[7]

Yongchang Zhang, Haitao Yang, Bo Xia. Model predictive torque control of induction motor drives with reduced torque ripple. IET Electric Power Applications, 2015, 9(9): 595-604.
DOI Google Scholar
[8]

P Cortes, M P Kazmierkowski, R M Kennel, et al. Predictive control in power electronics and drives. IEEE Transactions on Industrial Electronics, 2008, 55(12): 4312-4324.
DOI Google Scholar
[9]

F Morel, X Lin-Shi, J Retif, et al. A comparative study of predictive current control schemes for a permanent-magnet synchronous machine drive. IEEE Transactions on Industrial Electronics, 2009, 56(7): 2715-2728.
DOI Google Scholar
[10]

S Vazquez, J Rodriguez, M Rivera, et al. Model predictive control for power converters and drives: Advances and trends. IEEE Transactions on Industrial Electronics, 2017, 64(2): 935-947.
DOI Google Scholar
[11]

H Miranda, P Cortes, J I Yuz, et al. Predictive torque control of induction machines based on state-space models. IEEE Transactions on Industrial Electronics, 2009, 56(6): 1916-1924.
DOI Google Scholar
[12]

Yongchang Zhang, Jianguo Zhu. A novel duty cycle control strategy to reduce both torque and flux ripples for DTC of permanent magnet synchronous motor drives with switching frequency reduction. IEEE Transactions on Power Electronics, 2011, 26(10): 3055-3067.
DOI Google Scholar
[13]

Yuanlin Wang, Xiaocan Wang, Wei Xie, et al. Deadbeat model-predictive torque control with discrete space-vector modulation for PMSM drives. IEEE Transactions on Industrial Electronics, 2017, 64(5): 3537-3547.
DOI Google Scholar
[14]

Yongchang Zhang, Jialin Jin, Lanlan Huang. Model-free predictive current control of PMSM drives based on extended state observer using ultralocal model. IEEE Transactions on Industrial Electronics, 2021, 68(2): 993-1003.
DOI Google Scholar
[15]

Xiaoguang Zhang, Zhihao Zhao, Yu Cheng, et al. Robust model predictive current control based on inductance and flux linkage extraction algorithm. IEEE Transactions on Vehicular Technology, 2020, 69(12): 14893-14902.
DOI Google Scholar
[16]

Huixian Liu, Shihua Li. Speed control for PMSM servo system using predictive functional control and extended state observer. IEEE Transactions on Industrial Electronics, 2012, 59(2): 1171-1183.
DOI Google Scholar
[17]

S Bibian, H Jin. Time delay compensation of digital control for DC switchmode power supplies using prediction techniques. IEEE Transactions on Power Electronics, 2000, 15(5): 835-842.
DOI Google Scholar
[18]

H T Moon, H S Kim, M J Youn. A discrete-time predictive current control for PMSM. IEEE Transactions on Power Electronics, 2003, 18(1): 464-472.
DOI Google Scholar
[19]

T Sebastian. Temperature effects on torque production and efficiency of PM motors using NdFeB magnets. IEEE Transactions on Industry Applications, 1995, 31(2): 353-357.
DOI Google Scholar
[20]

M Khalilzadeh, S Vaez-Zadeh, M S Eslahi. Parameter-free predictive control of IPM motor drives with direct selection of optimum inverter voltage vectors. IEEE Transactions on Power Electronics, 2021, 9(1): 327-334.
DOI Google Scholar
[21]

F Tinazzi, P G Carlet, S Bolognani, et al. Motor parameter-free predictive current control of synchronous motors by recursive least-square self-commissioning model. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9093-9100.
DOI Google Scholar
[22]

J Yang, W H Chen, S Li, et al. Disturbance/uncertainty estimation and attenuation techniques in PMSM drives: A survey. IEEE Transactions on Industrial Electronics, 2017, 64(4): 3273-3285.
DOI Google Scholar
[23]

Cheng Xu, Zaikun Han, Shuai Lu. Deadbeat predictive current control for permanent magnet synchronous machines with closed-form error compensation. IEEE Transactions on Power Electronics, 2020, 35(5): 5018-5030.
DOI Google Scholar
[24]

Y Inoue, Y Kawaguchi, S Morimoto, et al. Performance improvement of sensorless IPMSM drives in a low-speed region using online parameter identification. IEEE Transactions on Industry Applications, 2011, 47(2): 798-804.
DOI Google Scholar
[25]

Chengbo Yang, Bao Song, Yuanlong Xie, et al. Online parallel estimation of mechanical parameters for PMSM drives via a network of interconnected extended sliding-mode observers. IEEE Transactions on Power Electronics, 2021, 36(10): 11818-11834.
DOI Google Scholar
[26]

Yu Yao, Yunkai Huang, Fei Peng, et al. An improved deadbeat predictive current control with online parameter identification for surface-mounted PMSMs. IEEE Transactions on Industrial Electronics, 2020, 67(12): 10145-10155.
DOI Google Scholar
[27]

D Q Dang, M S Rafaq, H H Choi, et al. Online parameter estimation technique for adaptive control applications of interior PM synchronous motor drives. IEEE Transactions on Industrial Electronics, 2016, 63(3): 1438-1449.
DOI Google Scholar
[28]

Y Abdel-Rady, I Mohamed, E F El-Saadany. An improved deadbeat current control scheme with a novel adaptive self-tuning load model for a three-phase PWM voltage-source inverter. IEEE Transactions on Industrial Electronics, 2007, 54(2): 747-759.
DOI Google Scholar
[29]

N Jabbour, C Mademlis. Online parameters estimation and autotuning of a discrete-time model predictive speed controller for induction motor drives. IEEE Transactions on Power Electronics, 2019, 34(2): 1548-1559.
DOI Google Scholar
[30]

S Kwak, U Moon, J Park. Predictive-control-based direct power control with an adaptive parameter identification technique for improved AFE performance. IEEE Transactions on Power Electronics, 2014, 29(11): 6178-6187.
DOI Google Scholar
[31]

Xiaoguang Zhang, Liang Zhang, Yongchang Zhang. Model predictive current control for PMSM drives with parameter robustness improvement. IEEE Transactions on Power Electronics, 2019, 34(2): 1645-1657.
DOI Google Scholar
[32]

M Mehreganfar, M H Saeedinia, S A Davari, et al. Sensorless predictive control of AFE rectifier with robust adaptive inductance estimation. IEEE Transactions on Industrial Informatics, 2019, 15(6): 3420-3431.
DOI Google Scholar
[33]

A Bartoszewicz, K Adamiak. Discrete-time sliding-mode control with a desired switching variable generator. IEEE Transactions on Automatic Control, 2020, 65(4): 1807-1814.
DOI Google Scholar
[34]

Bo Xu, Lei Zhang, Wei Ji. Improved non-singular fast terminal sliding mode control with disturbance observer for PMSM drives. IEEE Transactions on Transportation Electrification, 2021, 7(4): 2753-2762.
DOI Google Scholar
[35]

Zheng Li, Fengxiang Wang, Dongliang Ke, et al. Robust continuous model predictive speed and current control for PMSM with adaptive integral sliding-mode approach. IEEE Transactions on Power Electronics, 2021, 36(12): 14398-14408.
DOI Google Scholar
[36]

M Fliess, C Join. Model-free control. International Journal of Control, 2013, 86(12): 2228-2252.
DOI Google Scholar
[37]

C Lin, T Liu, J Yu, et al. Model-free predictive current control for interior permanent-magnet synchronous motor drives based on current difference detection technique. IEEE Transactions on Industrial Electronics, 2014, 61(2): 667-681.
DOI Google Scholar
[38]
Y Zhang, W Shen, H Yang, et al. An improved model-free predictive current control method for PMSM drives based on extended control set and fast current difference updating. 2022 IEEE Energy Conversion Congress and Exposition (ECCE), October 09-13, 2022, Detroit, MI, USA. IEEE, 2022: 1-8.
DOI
[39]

Yongchang Zhang, Tao Jiang. Robust predictive stator current control based on prediction error compensation for a doubly fed induction generator under nonideal grids. IEEE Transactions on Industrial Electronics, 2022, 69(5): 4398-4408.
DOI Google Scholar
[40]

Y Zhang, D Xu, J Liu, et al. Performance improvement of model predictive current control of permanent magnet synchronous motor drives. IEEE Transactions on Industry Applications, 2017, 53(4): 3683-3695.
DOI Google Scholar
Publication history
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Publication history

Received: 17 April 2022
Revised: 31 July 2022
Accepted: 25 October 2022
Published: 30 June 2023
Issue date: June 2023

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© 2023 China Machinery Industry Information Institute
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