Direct torque control of dual star induction motor using a fuzzy-PSO hybrid approach

Boukhalfa, Ghoulemallah; Belkacem, Sebti; Chikhi, Abdesselem; Benaggoune, Saïd

doi:10.1016/j.aci.2018.09.001

Cited by 26 publications

(14 citation statements)

References 35 publications

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“… Boukhalfa et al [43] presented the (PSO) algorithm in conjunction with the fuzzy system to make an optimized tuning of a controller (PID) in DTC control loops. of the double star induction motor.…”

Section: Prior Workmentioning

confidence: 99%

Interval Type-2 Fuzzy Logic-Second Order Sliding Mode Based Fault Detection and Active Fault-Tolerant Control of Brushless DC Motor

Dilmi¹,

Bouguerra²,

Djrioui³

et al. 2021

JESA

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This paper addresses the detection of the short-circuit faults and the active fault tolerant control (AFTC) of the brushless direct current motor (BLDCM) based on the interval type-2 fuzzy-second order sliding mode. In this article, the main idea consists of using an algorithm to detect the fault in an electric current. This algorithm corrects the detected fault. In this study, a hybrid technique of fault tolerant control is proposed. This technique based on interval type 2 fuzzy logic and second order sliding mode. Also, it facilitates the procedures for setting and controlling the velocity of BLDCM. For that, a dynamic model for direct current has been established. Furthermore, short circuit faults have also been introduced between turns to test the robustness of the control laws. Finally, a theoretical analysis is presented and the simulations are presented in order to validate the proposed control strategy. The proposed AFTC can then achieve favorable tracking performance.

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Section: Prior Workmentioning

confidence: 99%

Interval Type-2 Fuzzy Logic-Second Order Sliding Mode Based Fault Detection and Active Fault-Tolerant Control of Brushless DC Motor

Dilmi¹,

Bouguerra²,

Djrioui³

et al. 2021

JESA

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“…Therefore, a fitness function is defined as: Fig. 8 The concept of a searching point by PSO [27]. Fig.…”

Section: Construction Of the Fitness Functionmentioning

confidence: 99%

“…Block diagram of three-level Hysteresis Band velocity of the particle v k which can be represented by the concept of velocity as shown inFig. 8[27].The velocity of each particle can be modified by Eq. (33):…”

mentioning

confidence: 99%

Optimal DTC Control Strategy of DFIG Using Variable Gain PI and Hysteresis Controllers Adjusted by PSO Algorithm

Amer

Miloudi

Lakdja

2019

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

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This paper presents an optimal Direct Torque Control (DTC) strategy for Doubly Fed Induction Generator based wind turbine. The proposed strategy is considered based on Particle Swarm Optimization (PSO) Algorithm. The PSO is found to be robust and fast in solving nonlinear problems. Motivation for application of PSO approach is to overcome the limitation of the conventional controllers design, which cannot guarantee satisfactory control performance when designed by trial and error. In this work PSO algorithm was used to adjust the hysteresis torque and flux comparators bandwidths and to tune the parameters of Variable Gain PI (VGPI) controller designed for Maximum Power Point Tracking (MPPT) speed control of wind turbine to ensure high performance torque control. The optimal control strategy is considered in detail and it is shown that the use of the optimized controllers reduces rotor flux and electromagnetic torque ripples and improves the system dynamic performances. The effectiveness of the proposed direct torque control based on PSO algorithm (optimal DTC) method is illustrated through simulations on 1.5 MW DFIG based wind turbine. Simulation results illustrate the improved performances of optimal DTC compared with the conventional DTC.

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“…More specific publications are found in electric machine drives; in [16], a multi-objective particle swarm optimization algorithm was used in vector control drive to improve PI parameters of the speed controller to achieve a fast response of rotor speed and reduce torque ripple. Furthermore, the techniques which use hybridization occupy more and more place in the literature, as in [17] where the paper presents the PSO algorithm in conjunction with the fuzzy logic method to achieve an optimized tuning of a PID controller in a DTC control scheme. Or in [18] where the authors presented a speed and voltage PI controller's tuning algorithm using GA-PSO in vector control of an IM.…”

Section: Introductionmentioning

confidence: 99%

Hybrid bacteria foraging-particle swarm optimization algorithm in DTC performance improving for induction motor drive

Rezgui

Benalla

Bouhebel

2021

IJEECS

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<p dir="ltr"><span>This paper presents a hybrid algorithm that combines the particle swarm optimization method with the bacteria foraging technique, named: BF-PSO. The aim is to achieve more efficient and precise parameters determination of the regulators that leads to performance improvement in the speed-loop control of an induction motor (IM) implemented in a direct torque control (DTC). The approach consists of tuning the proportional-integral (PI) parameters that meet high dynamics and tracking behavior using the hybrid BF-PSO algorithm. </span>Investigations have been completed with Matlab/Simulink and several performance tests are conducted. The comparison results are exposed with the most used indices in the controllers' tuning with optimization techniques. It will be shown that the presented technique presents better quality results compared to the conventional method of calculated PI.</p><div><span><br /></span></div>

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Direct torque control of dual star induction motor using a fuzzy-PSO hybrid approach

Cited by 26 publications

References 35 publications

Interval Type-2 Fuzzy Logic-Second Order Sliding Mode Based Fault Detection and Active Fault-Tolerant Control of Brushless DC Motor

Interval Type-2 Fuzzy Logic-Second Order Sliding Mode Based Fault Detection and Active Fault-Tolerant Control of Brushless DC Motor

Optimal DTC Control Strategy of DFIG Using Variable Gain PI and Hysteresis Controllers Adjusted by PSO Algorithm

Hybrid bacteria foraging-particle swarm optimization algorithm in DTC performance improving for induction motor drive

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