Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

<b> </b>This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control...

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Main Authors: Meng Shao, Yongting Deng, Hongwen Li, Jing Liu, Qiang Fei
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/10/1857
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author Meng Shao
Yongting Deng
Hongwen Li
Jing Liu
Qiang Fei
author_facet Meng Shao
Yongting Deng
Hongwen Li
Jing Liu
Qiang Fei
author_sort Meng Shao
collection DOAJ
description <b> </b>This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.
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spelling doaj.art-c253722156ec428fa1672ffab9c71da42022-12-22T01:56:41ZengMDPI AGEnergies1996-10732019-05-011210185710.3390/en12101857en12101857Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSMMeng Shao0Yongting Deng1Hongwen Li2Jing Liu3Qiang Fei4Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China<b> </b>This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.https://www.mdpi.com/1996-1073/12/10/1857model predictive controlparameter identificationextended sliding mode observerPMSM
spellingShingle Meng Shao
Yongting Deng
Hongwen Li
Jing Liu
Qiang Fei
Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
Energies
model predictive control
parameter identification
extended sliding mode observer
PMSM
title Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
title_full Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
title_fullStr Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
title_full_unstemmed Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
title_short Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM
title_sort sliding mode observer based parameter identification and disturbance compensation for optimizing the mode predictive control of pmsm
topic model predictive control
parameter identification
extended sliding mode observer
PMSM
url https://www.mdpi.com/1996-1073/12/10/1857
work_keys_str_mv AT mengshao slidingmodeobserverbasedparameteridentificationanddisturbancecompensationforoptimizingthemodepredictivecontrolofpmsm
AT yongtingdeng slidingmodeobserverbasedparameteridentificationanddisturbancecompensationforoptimizingthemodepredictivecontrolofpmsm
AT hongwenli slidingmodeobserverbasedparameteridentificationanddisturbancecompensationforoptimizingthemodepredictivecontrolofpmsm
AT jingliu slidingmodeobserverbasedparameteridentificationanddisturbancecompensationforoptimizingthemodepredictivecontrolofpmsm
AT qiangfei slidingmodeobserverbasedparameteridentificationanddisturbancecompensationforoptimizingthemodepredictivecontrolofpmsm