Feedforward Decoupling Control of Interior Permanent Magnet Synchronous Motor With Genetic Algorithm Parameter Identification

Pan, Yanfei; Liu, Xin; Zhu, Yilin; Liu, Bo; Li, and Zhongshu

doi:10.2528/pierm21032903

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Many various areas such as electric vehicles, aerospace, numerical control systems, and wind power generation are highly dependent on the permanent magnet synchronous motors (PMSM) due to small volume, light weight, high efficiency, high power factor, fast response, wide speed range, and good accuracy [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

High-order Supper-twisting Based Terminal Sliding Mode Control Applied on Three Phases Permanent Synchronous Machine

Karboua

Toual

Kouzou

et al. 2023

Period. Polytech. Elec. Eng. Comp. Sci.

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Nowadays, research on electric drive control has become popular because hybrid methods to collect the advantages of individual controllers. Moreover, these methods aim to reach better performance and robust control even in the presence of uncertainties and disturbances which are typically evident in high-speed dynamics where the influence of external disturbances and modeling errors are more evident. Therefore, in this paper, a novel hybrid controller is proposed between the super-twisting algorithm based on high order design (HO-STA) and terminal sliding mode control (T-SMC) applied on a permanent magnet synchronous motor PMSM. Whereas, it accounts to deal with the weaknesses of both terminal sliding mode control and super twisting algorithm (STA) and at the same time combining their advantages; furthermore, it provides exceptional characteristics, including fast finite-time convergence, stabilization of the performance and its reaching law developer based on new design which contributes to reducing the chattering problems afflicted by C-SMC. This proposed hybrid technique contributes to gaining robust control under variation between slow, medium, and high speed levels, no matter what load torque is applied or whatever PMSM parameters change. Moreover, it also offers optimum performance characteristics such as smaller settling time and steady state error. Whereas, the control efficiency is demonstrated by Matlab/Simulink simulation to confirm our design parameters.

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Section: Introductionmentioning

confidence: 99%

High-order Supper-twisting Based Terminal Sliding Mode Control Applied on Three Phases Permanent Synchronous Machine

Karboua

Toual

Kouzou

et al. 2023

Period. Polytech. Elec. Eng. Comp. Sci.

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show abstract

“…In [6], a modified model predictive control method with the virtual model was proposed to reduce the dynamic tracking error of the position loop and the dynamic tracking error and stability time by generating a virtual reference. Adaptive control methods were adopted in [8][9][10][11][12]. In [8], a feedforward control scheme based on an adaptive observer was proposed for tracking problems with unknown mechanical parameters and unknown load torque.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Load Simulation Algorithm Based on an Inertia Simulation Predictive Model

Lin

Wang

et al. 2022

Applied Sciences

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In this study, an electric dynamic load simulation system (EDLSS) algorithm was proposed based on an inertia simulation predictive model to mitigate strong-coupling torque disturbance and load torque fluctuation caused by the change in the motion state of a bearing system. First, the inertia simulation model was proposed by combining the dynamic equations of both the EDLSS and the target system. The aforementioned inertia simulation model converted the conventional realisation method of the inertia simulation into the tracking of the motion characteristics for the target system under the same working conditions. Next, based on the aforementioned inertia simulation model while considering the strong-coupling torque effect and motor braking state disturbance as two influential factors, an inertia simulation predictive model and a load simulation algorithm were proposed. The predicted speed calculated by the predictive model was consistent with the dynamic characteristics of the target system under the same working conditions and input into the control loop. Based on the analysis of the braking state and power model of the permanent magnet synchronous motor, an energy feedback control method was proposed to improve EDLSS stability caused by the braking state of the loading motor. Finally, the experimental data revealed that the maximum speed fluctuation range of the loading motor was approximately 7.5, which was 84% lower than the range before the application of the aforementioned algorithm, which was about 46.8. Furthermore, the maximum range of the torque ripple was close to 1.5, which was 75% lower than before, which was roughly 6. All experimental data were consistent with simulation data.

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Sensorless fuzzy control algorithm for permanent magnet synchronous motor based on particle swarm optimization parameter identification and harmonic extraction

Zhang,

Qing,

Liu

et al. 2024

Journal of Electromagnetic Waves and Applications

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Feedforward Decoupling Control of Interior Permanent Magnet Synchronous Motor With Genetic Algorithm Parameter Identification

Cited by 7 publications

References 10 publications

High-order Supper-twisting Based Terminal Sliding Mode Control Applied on Three Phases Permanent Synchronous Machine

High-order Supper-twisting Based Terminal Sliding Mode Control Applied on Three Phases Permanent Synchronous Machine

A Dynamic Load Simulation Algorithm Based on an Inertia Simulation Predictive Model

Sensorless fuzzy control algorithm for permanent magnet synchronous motor based on particle swarm optimization parameter identification and harmonic extraction

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