Model-Free Predictive Current Control for Interior Permanent-Magnet Synchronous Motor Drives Based on Current Difference Detection Technique

Lin, Cheng-Kai; Liu, Tian‐Hua; Yu, Jen‐te; Fu, Li-Chen; Hsiao, Chieh-Fu

doi:10.1109/tie.2013.2253065

Cited by 311 publications

(178 citation statements)

References 44 publications

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“…Such parameter mismatches can bring different degrees of prediction error, which may further lead to wrong selection of optimal voltage vector and deteriorate system control performance. Many published papers have proposed methods to solve this problem, including designing model-free prediction algorithm [19,20], identifying parameters online [9,21,22], and constructing observers to estimate the influence of parameter deviations [23][24][25]. However, the model-free predictive control poses relatively high requirements for hardware implementation of the drive system, while the latter two categories are prone to making control algorithms complex, which may be not suitable for the real-time implementation and may even result in instability of the system.…”

Section: Introductionmentioning

confidence: 99%

Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs

Huang

Niu

et al. 2018

Energies

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Finite-control-set model predictive current control (FCS-MPCC) has been widely investigated in the field of motor control. When the discrete motor prediction model is not obtained accurately, prediction error often occurs, which can result in improper determinations of optimal voltage vectors and can further affect the control performance of motor systems. However, papers evaluating the motor control performance employing FCS-MPCC rarely consider prediction error and its utilization to weaken the influence of inaccurate prediction model. This paper investigates in depth the prediction error caused by three influencing factors from the perspective of model accuracy-discretization method, prediction stepsize, and parameter mismatch. Firstly, the evaluation index, prediction error, is defined and its formulas considering the above three factors are derived based on interior permanent magnet synchronous motor (IPMSM). Then, the theoretical analysis of prediction error is provided. Finally, experimental results of an IPMSM drive system are presented to verify and complement the theoretical analysis. Both the theoretical analysis and experimental results fully elaborate the prediction error, which can offer practical guidelines for the evaluation and improvement of motor control performance, especially for FCS-MPCC in IPMSM applications.

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Section: Introductionmentioning

confidence: 99%

Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs

Huang

Niu

et al. 2018

Energies

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“…The single-voltage-vector model-free predictive current control (SVV-MFPCC) [19][20][21][22][23] has recently received some attention, as it does not rely on system's mathematical models and parameters, nor on the back EMFs. As such, the SVV-MFPCC exhibits better current-tracking performance thanks to its lesser sensitivity to parameter variations.…”

Section: Introductionmentioning

confidence: 99%

A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems

Lin

Huang

et al. 2018

Energies

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For current control in power conversion and motor drive systems, there exist three classic methods in the literature and they are the hysteresis current control (HCC), the sine pulse-width modulation (SPWM), and the space vector pulse width modulation (SVPWM). HCC is easy to implement, but has relatively large current harmonic distortion as the disadvantage. On the other hand, the SPWM and SVPWM use modulation technique, commonly together with at least one proportional-integral (PI) regulator to reduce load current ripples, and hence demanding more computation time. This paper aims to improve the performance of a recently proposed new current control method-the single-voltage-vector model predictive current control (SVV-MPCC), for synchronous reluctance motor (SynRMs) drives. To that end, a dual-voltage-vector model-free predictive current control (DVV-MFPCC) for SynRMs is proposed. Unlike the SVV-MPCC that applies only a single voltage vector per sampling period, the proposed DVV-MFPCC is capable of providing two successive segmentary current predictions in the next sampling period through all possible combinations from any two candidate switching states increasing the number of applicable switching modes from seven to nineteen and reducing the prediction error effectively. Moreover, the new control does not utilize any parameters of the SynRM nor its mathematical model. The performance is effectively enhanced compared to that of SVV-MPCC. The working principle of the DVV-MFPCC will be detailed in this paper. Finally, the SVV-MPCC, the single-voltage-vector model-free predictive current control (SVV-MFPCC), the dual-voltage-vector model predictive current control (DVV-MPCC), and the DVV-MFPCC are realized to control the stator currents of SynRM through a 32-bit microcontroller TMS320F28377S. Experimental results are provided to validate the new method and verify that the DVV-MFPCC performs better than do the SVV-MPCC, the SVV-MFPCC, and the DVV-MPCC.

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“…Moreover, the cross-coupling terms between dq axis and synchronous frame system have not been taken into account. Many other attempts are proposed and discussed several techniques in order to improve the efficiency and the performance of APF [24][25][26][27][28][29][30][31][32][33][34][35]. In [36], Vatani et al proposed finite control set MPC based on p-q theory to control a three phase Neutral Point Clamped multi-level converter to act as a shunt APF.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control for Shunt Active Power Filter in Synchronous Reference Frame

Al-Othman¹,

AlSharidah²,

Ahmed³

et al. 2016

Journal of Electrical Engineering and Technology

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-This paper presents a model predictive control for shunt active power filters in synchronous reference frame using space vector pulse-width modulation (SVPWM). The three phase load currents are transformed into synchronous rotating reference frame in order to reduce the order of the control system. The proposed current controller calculates reference current command for harmonic current components in synchronous frame. The fundamental load current components are transformed into dc components revealing only the harmonics. The predictive current controller will add robustness and fast compensation to generate commands to the SVPWM which minimizes switching frequency while maintaining fast harmonic compensation. By using the model predictive control, the optimal switching state to be applied to the next sampling time is selected. The filter current contains only the harmonic components, which are the reference compensating currents. In this method the supply current will be equal to the fundamental component of load current and a part of the current at fundamental frequency for losses of the inverter. Mathematical analysis and the feasibility of the suggested approach are verified through simulation results under steady state and transient conditions for non-linear load. The effectiveness of the proposed controller is confirmed through experimental validation.

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Model-Free Predictive Current Control for Interior Permanent-Magnet Synchronous Motor Drives Based on Current Difference Detection Technique

Cited by 311 publications

References 44 publications

Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs

Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs

A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems

Model Predictive Control for Shunt Active Power Filter in Synchronous Reference Frame

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