Investigating Electrical Drive Performance Employing Model Predictive Control and Active Disturbance Rejection Control Algorithms

Aboelhassan, Ahmed; Diab, Ahmed M.; Galea, Michael; Bozhko, Serhiy

doi:10.23919/icems50442.2020.9291218

Cited by 12 publications

(2 citation statements)

References 33 publications

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“…PMSM drive system is considered a multi-input multioutput nonlinear system, and its control behavior can be influenced by several uncertain factors during operation, such as parameters' variation, external load disturbance, cross coupling among dq current components, nonlinear dynamics, and unmodeled parameters of the system [5]. Additionally, the optimal performance of the PMSM electrical drive can be diminished if the time delay between feedback measurements and actuation is not considered.…”

Section: Introductionmentioning

confidence: 99%

Modulated Model Predictive Speed Controller for PMSM Drives Employing Voltage-Based Cost Function

Aboelhassan,

Wang,

Buticchi

et al. 2024

IEEE Open J. Ind. Electron. Soc.

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Section: Introductionmentioning

confidence: 99%

Modulated Model Predictive Speed Controller for PMSM Drives Employing Voltage-Based Cost Function

Aboelhassan,

Wang,

Buticchi

et al. 2024

IEEE Open J. Ind. Electron. Soc.

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“…However, the improvement of updating method would introduce additional noise and the corresponding compensations are still needed [11, 12]. What's more, because of the coordinate transformation, if the time‐delay can't be compensated completely, it would always cause current coupling in the SRF [13]. For this reason, another method is to introduce direct time delay compensation in SRF.…”

Section: Introductionmentioning

confidence: 99%

Complete decoupling compensation of three‐phase inverter with LCL filter in synchronous reference frame

Shi

Huang

Zheng

2022

IET Power Electronics

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A decoupling control strategy of three‐phase inverter, which can realize complete decoupling of the active and reactive current in the synchronous reference frame (SRF) is proposed here. There are two coupling factors of current loop in SRF, one is time delay caused by digital control, and the other is AC filter. Dynamic time delay compensation is applied to eliminate coupling caused by the first factor. The phase of the bridge leg voltage can be predicted. The difference between it and the phase of reference voltage which takes part in pulse width modulation (PWM) is the dynamic compensation angle, which can compensate the time delay. High‐order feedforward compensation is applied to eliminate coupling caused by the second factor. Complex vector model of the LCL filter is derived and the high‐order coupling coefficients can be offset by feedforward compensation. The coupling characteristics and compensation principles are analysed in detail. The system stability is discussed. Finally, the simulation and experimental results are given to verify the theoretical analysis.

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Model predictive control for energy efficient AC motor drives: An overview

Shahid,

Jin,

Abbasi

et al. 2024

IET Electric Power Appl

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State‐of‐the‐art model‐based predictive control techniques for AC motor drives are reviewed in this paper. A plethora of MPC algorithms with vast number of complex ideas has emerged in the last decade and this work makes an attempt to present those concepts in an intuitive, comprehensive and hierarchical manner. More emphasis is laid on finite control set model predictive control (FCS‐MPC) methods, especially predictive torque control (PTC) and predictive current control (PCC) because of their emergence as the prime focus of ongoing research in energy efficient drive control. The main focus of this review is to analyse the most recent work, signpost the future research directions, identify the core challenges and consolidate the ideas into a coherent and concise reference. A comprehensive classification based on actuation signals is presented and reviewed in detail. Then, the important challenges in MPC implementation, such as computational complexity reduction and delay compensation, weighting factor selection for multi‐objective cost functions, steady state performance and ripple reduction, parameter variations/model mismatching and achieving extended prediction horizons, are surveyed and most relevant solutions are reviewed. A detailed analysis of the last five years related work is given at the end and it is concluded that the future course seems to be diverting towards voltage vector selection with optimised phase, magnitude and duty ratios. Computational burden is still one of the main hurdle towards MPC proliferation and adaptation in AC drive control at the industrial level. However, with advent of high speed and cheaper signal processors and development of efficient algorithms, MPC is rapidly becoming the control method of choice for energy‐efficient drive control.

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Investigating Electrical Drive Performance Employing Model Predictive Control and Active Disturbance Rejection Control Algorithms

Cited by 12 publications

References 33 publications

Modulated Model Predictive Speed Controller for PMSM Drives Employing Voltage-Based Cost Function

Modulated Model Predictive Speed Controller for PMSM Drives Employing Voltage-Based Cost Function

Complete decoupling compensation of three‐phase inverter with LCL filter in synchronous reference frame

Model predictive control for energy efficient AC motor drives: An overview

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