Adaptive finite‐control‐set model predictive current control for IPMSM drives with inductance variation

Chen, Zhuoyi; Qiu, Jian; Jin, Meng-Jia

doi:10.1049/iet-epa.2016.0861

Cited by 71 publications

(59 citation statements)

References 30 publications

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“…The continuous state equation of an IPMSM in d-q reference frame is expressed as [9]: Due to its implementation in microprocessors, such as digital signal processor (DSP), the continuous state Equation (1) has to be discretized for FCS-MPCC algorithm. The forward Euler approximation method is commonly utilized to obtain the discrete motor prediction model as [9]:…”

Section: Ipmsm Modelmentioning

confidence: 99%

“…The forward Euler approximation method is commonly utilized to obtain the discrete motor prediction model as [9]:…”

Section: Ipmsm Modelmentioning

confidence: 99%

“…It is well known that there are several approximation methods for differential equations [6]. In the field of motor control, forward Euler approximation method is widely used to obtain the discrete motor prediction model due to its simplicity and low computational burden for single-step prediction applications [7][8][9]. In Reference [10], a modified Euler integration method was adopted to achieve higher model accuracy, which actually transformed the implicit Tustin approximation to an explicit one by combining with forward Euler approximation.…”

Section: Introductionmentioning

confidence: 99%

“…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%

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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.

show abstract

Section: Ipmsm Modelmentioning

confidence: 99%

“…The forward Euler approximation method is commonly utilized to obtain the discrete motor prediction model as [9]:…”

Section: Ipmsm Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Huang

Niu

et al. 2018

Energies

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show abstract

“…It also permits the inclusion of system constraints and nonlinearities, if any, in the given model [5,6].…”

Section: Introductionmentioning

confidence: 99%

Utilizing Sequential Action Control Method in GaN-Based High-Speed Drive for BLDC Motor

Niknejad¹,

Agarwal²,

Barzegaran³

2017

Machines

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This paper presents a hybrid model-based control algorithm that combines Model Predictive Control (MPC) and Sequential Action Control (SAC) deployed in a high-speed drive for Brushless DC (BLDC) motor by using a DC-DC converter with Gallium Nitride (GaN) switches. GaN FETs are selected because of their higher speed and lower power loss as compared with traditional Si switches. In the proposed framework, SAC processes the initial values of the control variables as well as their time of application and their duration in MPC loop. After receiving the underlying estimation of future contribution from SAC, MPC consolidates it with current input and predicts future control values by using the system state space model. This hybrid control conserves control effort and reduces sensitivity to initial conditions. In this way, converter's output voltage is controlled to produce the reference speed at the motor output. National Instrument PXIe-6356 module is utilized as the interface between software and hardware that is a multi-function, LabVIEW-compatible data acquisition device. The viability of the proposed hybrid optimization for the high-speed drive is confirmed numerically by utilizing MATLAB/Simulink and approved experimentally using a Gallium Nitride (GaN) half-bridge DC-DC converter.

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Sliding Mode Model-Free Predictive Current Control of PMSM with Direct Selection of Optimal Voltage Vector

J¹,

Deng²,

Wang³

et al. 2022

Lecture Notes in Electrical Engineering

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Adaptive finite‐control‐set model predictive current control for IPMSM drives with inductance variation

Cited by 71 publications

References 30 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

Utilizing Sequential Action Control Method in GaN-Based High-Speed Drive for BLDC Motor

Sliding Mode Model-Free Predictive Current Control of PMSM with Direct Selection of Optimal Voltage Vector

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