Grey Prediction PI Control of Direct Drive Permanent Magnet Synchronous Wind Turbine

He, Shengxiang; Wang, Mingdong

doi:10.1109/ei250167.2020.9346881

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…D irect-drive permanent magnet synchronous generator (D-PMSG) is the hot spot of wind power development nowadays [1][2][3]. In harsh environments, D-PMSG systems may be susceptible to demagnetization failures caused by elevated temperatures, chemical corrosion, mechanical vibrations, and other factors [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Fault-tolerant Control of D-PMSG Demagnetization Based on Linear Active Disturbance Rejection Controller

Luo,

Liu,

Peng

et al. 2024

PIER M

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When demagnetization occurs, direct-drive permanent magnet synchronous wind generator exhibits problems of poor dynamic performance, weak immunity to disturbances and speed fluctuations. Aiming at these problems, this paper proposes a cascaded linear active disturbance rejection control method. First, the mathematical models of the generator during normal operation and demagnetization are described. Second, the linear active disturbance rejection controller (LADRC) for the speed and current loops is designed. The compensation for demagnetization disturbances at the speed loop's input is enabled by the control approach. The current output of the speed loop is imported as a rated value into the LADRC of the current loop. At the same time, the current is compensated at the input. Compensated speed and current accurately track the given values, and the goal of achieving demagnetization fault tolerance is met. Finally, this method is compared with dual-loop Proportional Integral (PI) control. The experimental results affirm that, under this control method, when demagnetization occurs, the speed fluctuation is reduced by 95.7%, the current response time decreased from 0.01 seconds to 0.001 seconds, and the electromagnetic torque ripple amplitude reduced by 50%. These experimental results fully validate the heightened fault tolerance and resistance to interference exhibited by the method advocated in this paper.

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Section: Introductionmentioning

confidence: 99%

Fault-tolerant Control of D-PMSG Demagnetization Based on Linear Active Disturbance Rejection Controller

Luo,

Liu,

Peng

et al. 2024

PIER M

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“…D-PMSG wind power generation system does not need excitation devices, resulting in higher power generation efficiency and stability. D-PMSG wind power generation system will become the mainstream type of wind power generation [3,4].…”

Section: Introductionmentioning

confidence: 99%

A Fault-Tolerant Control Strategy for D-PMSG Wind Power Generation System

Luo¹,

Peng²,

Zhang³

et al. 2022

PIER C

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Aiming at the problem of motor speed decrease in direct-drive permanent magnet synchronous generator (D-PMSG) wind power generation system after permanent magnet (PM) demagnetization faults, a demagnetization fault-tolerant control strategy in D-PMSG wind power generation system is proposed. Firstly, the D-PMSG mathematical model is described in normal and demagnetization. Secondly, an extended Kalman filter (EKF) observer is designed to observe the PM flux online. Then, flux linkage parameters are introduced into the two-vector model predictive faulttolerant control so that the increase of stator current is controlled within the limit range. Meanwhile, the motor speed can follow the change of the given speed. In addition, the improved Luenberger mechanical torque observer is designed in the speed outer ring to deal with the vibration caused by unstable wind speed. Finally, compared with the dual-closed-loop Proportional Integral (PI) control, the experimental results show that the demagnetization fault-tolerant control strategy has smaller speed overshoot and smaller speed fluctuation when the mechanical torque changes. The method can maintain the speed balance when the PM demagnetization faults occur and have stronger fault tolerance and antiinterference ability.

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“…From his first work, there are many applications proposed in literature, such as fields of environmental engineering, water conservancy, business management, electrical machinery, civil engineering, industry, transportation, etc. The complete grey theory is continuously developed including grey modeling [2], correlation analysis, grey control [3], grey prediction [4], grey decision-making [5,6], etc. To realize the prediction of data systems, the grey model GM (1,1) has been proposed, e.g., [7].…”

Section: Introductionmentioning

confidence: 99%

Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

Chen

Chiu

Lee³

2021

Axioms

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Mobile robots are widely used in many applications, while various types of mobile robots and their control researches have been proposed in literature. Since swarm robots have higher flexibility and capacity for teamwork, this paper presents a grey estimator-based tracking controller for formation trajectory tracking of swarm robots. First, wheel-type mobile robots are used and modeled for the controller design. Then, a grey dynamic estimator is developed to estimate the environmental disturbance and model uncertainty for linear feedback compensation. As a result, the asymptotic trajectory tracking is assured, so that the application on the swarm robot formation is achieved for a multi-agent system. The computational complexity is slightly reduced by the design. Finally, in order to verify the reliability of swarm robot formation, several types of formation are maintained by the grey estimator-based feedback linearization controller.

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Grey Prediction PI Control of Direct Drive Permanent Magnet Synchronous Wind Turbine

Cited by 5 publications

References 2 publications

Fault-tolerant Control of D-PMSG Demagnetization Based on Linear Active Disturbance Rejection Controller

Fault-tolerant Control of D-PMSG Demagnetization Based on Linear Active Disturbance Rejection Controller

A Fault-Tolerant Control Strategy for D-PMSG Wind Power Generation System

Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

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