Simplified Fault-Tolerant Model Predictive Control for a Five-Phase Permanent-Magnet Motor With Reduced Computation Burden

Tao, Tao; Zhao, Wenxiang; Du, Yuxuan; Cheng, Yu; Zhu, Jihong

doi:10.1109/tpel.2019.2934578

Cited by 78 publications

(31 citation statements)

References 30 publications

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“…The comparison of ( 13) with (15) shows that the computational complexity of the current prediction model calculated using the approximation principle is reduced to some extent. Similarly, a simplified model of the stator flux can be obtained:…”

Section: B Simplification Of Prediction Modelmentioning

confidence: 99%

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A Predictive Torque Control Method for Dual Three-Phase Permanent Magnet Synchronous Motor Without Weighting Factor

Zhang

Sun

et al. 2021

IEEE Access

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Section: B Simplification Of Prediction Modelmentioning

confidence: 99%

“…Among them, MPC has developed rapidly in recent years. MPC technology has been applied to motors, and the performance of the motors is very good [11]- [15]. The advantages of MPC are simpler control structure [16], fast response speed [17], and ease to modify the restriction conditions [18].…”

Section: Introductionmentioning

confidence: 99%

A Predictive Torque Control Method for Dual Three-Phase Permanent Magnet Synchronous Motor Without Weighting Factor

Zhang

Sun

et al. 2021

IEEE Access

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show abstract

“…An example of implementing FCS-MPC minimizes the total current harmonic content [73]. In addition, a fixed switching frequency fault tolerant control can be achieved by integrating the virtual voltage vectors with predictive method [97].…”

Section: E Fault-tolerant Operationmentioning

confidence: 99%

Vision, Challenges, and Future Trends of Model Predictive Control in Switched Reluctance Motor Drives

et al. 2021

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Switched Reluctance Motors (SRMs) have become a popular alternative to replace permanent magnet machines in high-performance emerging applications such as automotive and aerospace. However, its market attractiveness is limited by the difficulty in control given its nonlinear behaviour. Model predictive control (MPC) is a promising solution to deal with this problem as per its notable features to deal with complex systems, nonlinearities and constraints. Still, the applications in SRMs are at an early stage compared to other drives. This paper aims to discuss the recent advancements and challenges in MPC for SRMs and a vision of its future developments and applications. The article describes the main difficulties in SRM control and the different approaches adopted to date by MPC to solve them. It also analyzes the control objectives that should still be considered in SRM drives, their particular challenges and how recent MPC developments in other AC drives can be adapted to the SRM case. The paper then proposes a roadmap of future works to achieve a unified and reliable control strategy that boosts SRM to outperform other drives, relating the control objectives to its potential applications.

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“…The most up-to-date research in this field is still showing a persistent interest to highlight the various benefits of this promising technology in various industrial applications such as automotive, aerospace, ship propulsion, and offshore wind energy generation systems [2]. Consequently, recent literature has discussed several challenges such as control, machine design, [3], [4] parameter identifications [5], fault detection and post-fault operation [6], [7] as well as some other innovative applications [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Predictive Current Control of Six-Phase Induction Motor With Different Winding Configurations

et al. 2021

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Asymmetrical six-phase (A6P) induction motor-based drives can be considered as a wellestablished employed technology in high-power safety-critical industry sectors. Of the different control techniques proposed for multiphase machines, model predictive control (MPC) has recently been favored thanks to its simplicity, rapid dynamic response, and flexibility to define new control objectives. One of the main operating challenges when employing MPC to A6P induction machine is the poor quality of the phase current waveform due to the relatively low impedance of the secondary subspace. Although different controller structures have been introduced in the available literature to mitigate this problem, most of the available proposals, if not affecting the dc-link voltage utilization, will likely add to the control complexity. From the stator winding layout perspective, this paper attempts to investigate the effect of different winding configurations of six-phase stators with isolated neutral arrangements on the performance of predictive current control (PCC). This study shows that the winding configuration affect the mapping of the 64 available voltage vectors to the and subspaces, the induced current ripples, and the required weighting factor employed in PCC. The theoretical findings have experimentally been validated using a 1kW twelve-phase machine that can externally be reconnected to form any of the three available six-phase winding configurations.INDEX TERMS six-phase, dual three-phase, asymmetrical, symmetrical, predictive current control, voltage space decomposing.

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Simplified Fault-Tolerant Model Predictive Control for a Five-Phase Permanent-Magnet Motor With Reduced Computation Burden

Cited by 78 publications

References 30 publications

A Predictive Torque Control Method for Dual Three-Phase Permanent Magnet Synchronous Motor Without Weighting Factor

A Predictive Torque Control Method for Dual Three-Phase Permanent Magnet Synchronous Motor Without Weighting Factor

Vision, Challenges, and Future Trends of Model Predictive Control in Switched Reluctance Motor Drives

Assessment of Predictive Current Control of Six-Phase Induction Motor With Different Winding Configurations

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