Double star induction machine using nonlinear integral backstepping control

Abden, Abdallah; Bouchetta, A.; Boughazi, Othmane; Baghdadi, A.; Bousserhane, L K.

doi:10.11591/ijpeds.v10.i1.pp27-40

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…The outer loop provides the VCVs (the references of currents) via the reactive and active power control. While the inner loop provides the actual control variables (rotor voltages) [17,18].…”

Section: Proposed Control Strategies 31 Msc Controlmentioning

confidence: 99%

Robust coordinated control using backstepping of flywheel energy storage system and DFIG for power smoothing in wind power plants

Nadour¹,

Essadki²,

Nasser³

et al. 2019

IJPEDS

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<p>This paper presents a robust coordinated control of a flywheel energy storage system (FESS) and a doubly fed induction generator (DFIG) based wind energy conversion system (WECS), used to smooth the wind induced output power fluctuations. The overall system control combines field oriented control schemes and nonlinear backstepping approach applied first, to the machine side converter (MSC) to regulate the DFIG active and reactive power in order to ensure maximum power point tracking (MPPT) operation and a unity power factor at the point of common coupling (PCC). Then, to the grid side converter (GSC) to maintain a constant DC bus voltage. Finally, to the flywheel side converter (FSC) in way that allows the storage unit to serve as a buffer that stores energy in the case of excess power and retrieves it back into the output in the case of power deficiency. A numerical simulation using Matlab/Simulink software validates the effectiveness of the proposed control strategies in terms of dynamic response, improvement of generated power quality and robustness against parametric variation.</p>

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Section: Proposed Control Strategies 31 Msc Controlmentioning

confidence: 99%

Robust coordinated control using backstepping of flywheel energy storage system and DFIG for power smoothing in wind power plants

Nadour¹,

Essadki²,

Nasser³

et al. 2019

IJPEDS

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“…(ii) DSIM: the double star induction machine is composed of two parts, one is the stator and the other is the rotor. e stator of the DSIM is composed of two windings coupled in a star, each winding consists of three phases offset from each other by an angle of 2π⁄ 3 [31,32].…”

Section: Introductionmentioning

confidence: 99%

Operating of DSIM without Current and Speed Sensors Controlled by ADRC Control

Oumar

Ahmed

Cherkaoui

2022

Mathematical Problems in Engineering

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This paper presents an operation of the double start induction machine (DSIM) without current and speed sensors controlled by active disturbance rejection control (ADRC). The operation of the machine, without current and speed sensors, is an economic and simple method. The main advantages of this method are the reconstruction of stator current phases and rotor speed using only one DC voltage. The method is very simple and effective. It is based on the information provided by a DC voltage and the switching states of the converters to reconstruct the stator voltages. After we use two voltages observers to estimate the current stator and the rotor speed. The performance and the effectiveness of this method are verified under different conditions of simulations in MATLAB/Simulink. The results of the simulation prove the ability of this method to produce the same performances of DSIM with the current and speed sensors.

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“…The disadvantage of this method is that if the nonlinear components are removed incorrectly, it will adversely affect the control results and reduce the sustainability of the system. Other nonlinear control methods such as bakstepping [12][13][14], sliding mode control [15][16], the disadvantage of these methods is that there are harmonic oscillations.…”

Section: Introductionmentioning

confidence: 99%

The Neural Network-Combined Optimal Control System of Induction Motor

Trong¹

2019

IJECE

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<span lang="EN-US">This research aims to propose the optimal control method combined with the neuron network for an induction motor. In the proposed system, the induction motor is a nonlinear object which is controlled at each working point. At these working-points, the state equation of the induction motor is linear, so it is possible to apply the linear quadratic regular algorithm for the induction motor. Therefore, the parameters of the state feedback controller are the functions. The output-input relationships of these functions are set through the neural network. The numerical simulation results show that the quality of the control system of the induction motor is very high: The response speed always follows the desired speed with the short transition time and the small overshoot. Furthermore, the system is robust in the case of changing the load torque, and the parameters of the induction motor are incorrectly defined</span>

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Double star induction machine using nonlinear integral backstepping control

Cited by 5 publications

References 4 publications

Robust coordinated control using backstepping of flywheel energy storage system and DFIG for power smoothing in wind power plants

Robust coordinated control using backstepping of flywheel energy storage system and DFIG for power smoothing in wind power plants

Operating of DSIM without Current and Speed Sensors Controlled by ADRC Control

The Neural Network-Combined Optimal Control System of Induction Motor

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