Novel Compensation Strategy for Calculation Delay of Finite Control Set Model Predictive Current Control in PMSM

Gao, Jinqiu; Gong, Chao; Li, Wenzhen; Liu, Jinglin

doi:10.1109/tie.2019.2934060

Cited by 120 publications

(52 citation statements)

References 14 publications

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“…This method is called finite control set MPCC (FCS-MPCC) [14,15]. Comparatively speaking, because the latter strategy is so easy to understand and implement that it does not require the users to acquire an in-depth knowledge of the optimal control theory [16], FCS-MPCC methods are gaining increasing attention in the industry.…”

Section: Introductionmentioning

confidence: 99%

Robust Perturbation Observer-based Finite Control Set Model Predictive Current Control for SPMSM Considering Parameter Mismatch

Liu

Zhao

2019

Energies

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In order to improve the dynamics of the surface-mounted permanent magnet synchronous motors (SPMSM) used in servo systems, finite control set model predictive current control (FCS-MPCC) methods have been widely adopted. However, because the FCS-MPCC is a model-based strategy, its performance highly depends on the machine parameters, such as the winding resistance, inductance and flux linkage. Unfortunately, the parameter mismatch problem is common due to the measurement precision and environmental impacts (e.g., temperature). To enhance the robustness of the SPMSM FCS-MPCC systems, this paper proposes a Lundberg perturbation observer that is seldom used in the FCS model predictive control situations to remove the adverse effects caused by resistance and inductance mismatch. Firstly, the system model is established, and the FCS-MPCC mechanism is illustrated. Based on the machine model, the sensitivity of the control algorithm to the parameter mismatch is discussed. Then, the Luenberger perturbation observer that can estimate the general disturbance arising from the parameter uncertainties is developed, and the stability of the observer is analyzed by using the discrete pole assignment technique. Finally, the proposed disturbance observer is incorporated into the FCS-MPCC prediction plant model for real-time compensation. Both simulation and experiments are conducted on a three-phase SPMSM, verifying that the proposed strategy has marked control performance and strong robustness.

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Section: Introductionmentioning

confidence: 99%

Robust Perturbation Observer-based Finite Control Set Model Predictive Current Control for SPMSM Considering Parameter Mismatch

Liu

Zhao

2019

Energies

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“…In particular, the system ripples should be low. Whereas, there are many reasons that can cause high speed, torque or flux ripples in the practical applications, and these can be grouped into internal and external factors [17][18][19][20][21][22][23][24][25]. The internal factors mainly include; (1) the values of the parameters (e.g., stator inductance and resistance, etc.)…”

Section: Introductionmentioning

confidence: 99%

“…(2) weighting factor is not appropriate [18][19][20]; (3) control period is long in some applications [21]; (4) calculation delay reduces prediction accuracy [22]; and (5) the number of voltage candidates in the control set is not enough. Some of the external factors are summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the high-frequency disturbances arising from the inaccurate sensors are excluded, thereby ensuring that the magnitude of the ripples is limited. Compared to the existing ripple optimization methods in [17][18][19][20][21][22][23][24][25][26][27][28][29], the proposed ripple attenuation strategies are totally different, and the novelties are reflected in the following aspects:…”

Section: Introductionmentioning

confidence: 99%

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Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

et al. 2021

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Finite control set model predictive torque control (FCS-MPTC) strategy has been widely used in induction motor (IM) control due to its fast response characteristic. Although the dynamics of the FCS-MPTC method are highly commended, its steady-state performance—ripple deserves attention in the meantime. To improve the steady-state performance of the IM drives, this paper proposes an improved FCS-MPTC strategy, based on a novel fuzzy adaptive speed controller and an adaptive weighting factor, tuning strategy to reduce the speed, torque and flux ripples caused by different factors. Firstly, a discrete predicting plant model (PPM) with a new flux observer is established, laying the ground for achieving an FCS-MPTC algorithm accurately. Secondly, after analyzing the essential factors in establishing a fuzzy adaptive PI controller, with high ripple suppression capacity, an improved three-dimensional controller is designed. Simultaneously, the implementation procedures of the fuzzy adaptive PI controller-based FCS-MPTC are presented. Considering that a weighting factor must be employed in the cost function of an FCS-MPTC method, system ripples increase if the value of the weighting factor is inappropriate. Then, on that basis, a novel fuzzy adaptive theory-based weighting factor tuning strategy is proposed, with the real-time torque and flux performance balanced. Finally, both simulation and hardware-in-loop (HIL) test are conducted on a 1.1 kW IM drive to verify the proposed ripple reduction algorithms.

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“…During recent years, the finite control set model predictive control (FCS‐MPC) strategy has emerged as an attractive solution for permanent magnet synchronous motor (PMSM) and power converters due to its intuitive concept, great flexibility and fast dynamic response [1–3]. The FCS‐MPC predicts the future behaviour of the system states in each sampling instant based on the system model and selects the optimal actuation according to predefined optimization criteria (cost function) [4–6]. Compared to another predictive control techniques, one of the best features is the system non‐linearities and limitations can be incorporated directly into the system model.…”

Section: Introductionmentioning

confidence: 99%

Robust cascade‐free predictive speed control for PMSM drives based on Extended State Observer

2021

IET Electric Power Applications

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The direct predictive speed controller (DPSC) deals with the prediction of the motor speed based on precise mechanical parameters. However, the mechanical parameters are dependent on the practical applications and may not match with their actual values, which leads to inaccurate prediction of the motor behaviour and deteriorates the performance of the predictive algorithm. A three‐order Extended State Observer is designed for a permanent magnet synchronous motor to observe the unknown overall disturbance of the system and compensate the speed prediction error, which reduces the usage of the mechanical constants and improves the robustness of the system against parameter uncertainties, accurate mechanical parameters become unessential. To improve the current dynamics, by using proper weighting of the position angle observation error, along with the overall disturbance, a new current controller is incorporated in the control law of developed PSC strategy. The proposed strategy is evaluated through experimental results with a two‐level voltage source inverter. Finally, the proposed work is experimentally compared with a predictive speed control, by considering several performance indices.

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Novel Compensation Strategy for Calculation Delay of Finite Control Set Model Predictive Current Control in PMSM

Cited by 120 publications

References 14 publications

Robust Perturbation Observer-based Finite Control Set Model Predictive Current Control for SPMSM Considering Parameter Mismatch

Robust Perturbation Observer-based Finite Control Set Model Predictive Current Control for SPMSM Considering Parameter Mismatch

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

Robust cascade‐free predictive speed control for PMSM drives based on Extended State Observer

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