Interval type-2 fuzzy gain-adaptive controller of a Doubly Fed Induction Machine (DFIM)

Loukal, Keltoum; Benalia, Leila

doi:10.4314/jfas.v8i2.20

Cited by 4 publications

(4 citation statements)

References 12 publications

(20 reference statements)

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“…The DFIM mathematical model must be taken into account some simplify hypotheses to get a dynamic model make it possible to control the electrical system. [19].…”

Section: Description Of the Systemmentioning

confidence: 99%

Improvement of adaptive fuzzy control to adjust speed for a doubly fed induction motor drive (DFIM)

Brahim¹,

Bendjebbar²,

Lachtar³

2020

IJPEDS

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This paper presents the doubly fed induction motor (DFIM) speed control using adaptive fuzzy logic PI (AFLPI) controller to give better dynamic performances. Before the advent of modern technology, integral proportional based current controller is usually used due to its simplicity. But, the performance of closed-loop control is largely influenced by this type of speed and torque controllers used, as long as the PI controllers suffer from tuning problem. To overcome the problem, a new technique AFLPI based speed controller for direct field oriented control fed DFIM to get fast speed response and to minimize the torque ripple. The application of this type of control is very satisfactory to replace the conventional PI controller and, even the fuzzy logic PI (FLPI) controller. The performance of the field oriented controlled DFIM drive has simulated at different operating conditions using the AFLPI controller and the obtained results are compared with FLPI controller and conventional PI controller. Accordingly, an improvement in dynamic and robustness is clearly appears in AFLPI controller simulation results compared to the others aforementioned controllers. Simulation Results are presented for the three techniques using Matlab/Simulink to prove the dynamic performances and robustness.

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“…The DFIM mathematical model must be taken into account some simplify hypotheses to get a dynamic model make it possible to control the electrical system. [19].…”

Section: Description Of the Systemmentioning

confidence: 99%

Improvement of adaptive fuzzy control to adjust speed for a doubly fed induction motor drive (DFIM)

Brahim¹,

Bendjebbar²,

Lachtar³

2020

IJPEDS

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“…Those works by Al Mashhadany [22], Singh et al [9] made a comparison between type 2 and type 1 fuzzy logic control, and classic PID control of the brushless DC motor. Loukal and Benalia [23], and Ramya et al [24] conducted a comparision between the PID hybrid controllers with self-adjusting gains with fuzzy logic type 1 and 2, and classic PID regulators is made.…”

Section: Introductionmentioning

confidence: 99%

“…In the faultless mode, it is seen that the second-order sliding mode control is sufficient and it is better than the interval fuzzy logic type 2 control. the most difference between them is the interval type 2 fuzzy logic control possesses the higher energy consumption and too slow in computation [23,34]. But in the case of the existence of a fault, we see that the interval type 2 fuzzy logic control gives us good results compared to the second-order sliding mode control.…”

Section: Introductionmentioning

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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“…It is easy to design and implement, but it has difficulty in dealing with parameter variations, and load disturbances [10,11]. The control objective is to produce of control decoupled of the flux and the torque of the DSIM like DC motors [7], [12].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Field-Oriented Control Using Supervisory Type-2 Fuzzy Control for Dual Star Induction Machine

Rahali¹,

Zeghlache²,

Benalia³

2017

IJIES

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This paper proposes Interval Type-2 Fuzzy Gain-Adaptive PI (IT2FGAPI) controller based on direct field oriented control (DRFOC), to control the speed of a dual star induction machine (DSIM), to get a robust performance machine. We use IT2FGAPI for speed control of the DSIM corresponding to adapting the different gains Kp and Ki corresponding the different PI logic, PI of speed, PI of flux and the four PI of currents in a vector control mode. An interval type-2 fuzzy control system is used to adapt in real-time the controller gains, to generate the PI controller parameters, he gives a fast dynamic response with no overshoot, robust and their performances are insensible to parameter variations, at different dynamic operating such as sudden change in command speed, step change in load torque and some key parameters deviation. The simulations results obtained from MatLab/Simulink are finally presented and discussed; the obtained results show that the controller in enhancing the robustness of control systems with high accuracy.

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Interval type-2 fuzzy gain-adaptive controller of a Doubly Fed Induction Machine (DFIM)

Cited by 4 publications

References 12 publications

Improvement of adaptive fuzzy control to adjust speed for a doubly fed induction motor drive (DFIM)

Improvement of adaptive fuzzy control to adjust speed for a doubly fed induction motor drive (DFIM)

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

Adaptive Field-Oriented Control Using Supervisory Type-2 Fuzzy Control for Dual Star Induction Machine

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