Control strategy of a dual induction motor: Anti-slip control application

Achour, Tahar; Debbou, Mustapha; Pietrzak‐David, Maria

doi:10.1016/j.conengprac.2014.12.008

Cited by 12 publications

(3 citation statements)

References 21 publications

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“…Their control strategy was based on the time derivative of slip ratio and tractive force. Achour et al [37] introduced an average differential control as an anti-slip strategy in dealing with dual-induction motors that use as the railway traction system. Cooperative control was used to generate the voltage references introduced in the pulse-width modulation (PWM) block to reduce the number of control units.…”

Section: Control Strategies Based On the Slip Estimationmentioning

confidence: 99%

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Moaveni

Fathabadi

Molavi

2020

Asian Journal of Control

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This study proposes an anti-slip control system for electric trains based on the fuzzy logic theory, which prevents the wheels from slipping during the acceleration and simultaneously tracks the desired speed profile. To improve the control performance, the train longitudinal velocity and the slip ratio are estimated. By using a Field Oriented Control (FOC), the angular speed of the traction motor is controlled. The fuzzy control system determines the desired angular speed of the traction motor as the reference input of FOC to obtain the desired slip ratio and track the desired speed profile. Simulation results show the effectiveness of the control system in various wheel-rail surface conditions based on the real parameters of ER24PC locomotive.

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Section: Control Strategies Based On the Slip Estimationmentioning

confidence: 99%

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Moaveni

Fathabadi

Molavi

2020

Asian Journal of Control

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“…Velocity tracking research can be divided into two parts: [4] only considering speed tracking control, ignoring other factors; [5][6][7] considering the impact of wheel slipping when performing speed tracking control. [4,[8][9][10][11][12][13] Wheel slipping will cause a deviation in the speed between the train and the wheel. In severe cases, the train will derail.…”

Section: Introductionmentioning

confidence: 99%

“…An anti-slip control strategy for wheels based on average differential control was developed by Achour and Debbou. [11] For dual induction traction motors, the differential torque between traction motors could be eliminated. The strategy was tested on a semiphysical simulation platform with a mechanical railway load.…”

Section: Introductionmentioning

confidence: 99%

Freight Train Speed Active Disturbance Rejection Tracking and Wheel Anti-slip Based on T-S Fuzzy Neural Network

Chen

et al. 2022

Preprint

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A speed tracking control scheme is proposed for freight trains in this paper. This speed tracking scheme approach can prevent the wheel from slipping while controlling the traction motor to drive freight trains at an appropriate speed. Direct Torque Control (DTC) used by the HXD1 electric traction locomotive is applied in this strategy to control the asynchronous motor. Velocity tracking control is implemented by a Predictive Auto Disturbance Rejection Control (PADRC). Through an modified Smith estimator, this PADRC can predict the response of time-delay systems. In addition, an Unscented Kalman Filter (UKF) observer is designed. An adaptive parameter adjustment mechanism implemented by Affinity Propagation-Fuzzy Neural Network (AP-FNN) is also integrated into this observer. It is used to solve the problem that is difficult to measure the radial velocity and creep rate accurately. Using the anti-slip parameters obtained by this observer, the control scheme of anti-skid control is determined. Under wet and dry pavement conditions, an actual speed curve of a freight train is used to simulate and verify the effectiveness of this scheme.

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Freight train speed active disturbance rejection tracking and wheel anti-slip based on fuzzy neural network with DBO optimization

Yi,

Jiang,

et al. 2023

Electr Eng

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Control strategy of a dual induction motor: Anti-slip control application

Cited by 12 publications

References 21 publications

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Freight Train Speed Active Disturbance Rejection Tracking and Wheel Anti-slip Based on T-S Fuzzy Neural Network

Freight train speed active disturbance rejection tracking and wheel anti-slip based on fuzzy neural network with DBO optimization

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