Robust speed sensorless fuzzy control of the induction machine drive with adaptation of the rotor time constant supplied by photovoltaic solar energy

Larabi, Abdelkader; Amrane, A.; Boucherit, Mohamed Seghir

doi:10.1109/powereng.2013.6635819

Cited by 3 publications

(16 citation statements)

References 9 publications

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“…In this article, the membership functions are chosen as the triangular type, and the method of reasoning is considered as the max-min method, the defuzzification stage is done based on the gravity centre method, as it is frequently quoted in the literature and because they requiring less time computing will be also adopted in our work [8,9]. The format of the fuzzy control rule is described as "if E and Ec then u", whose fuzzy logic controller rules shown in Table Ⅰ.…”

Section: Self-tuning Fuzzy Controllermentioning

confidence: 99%

“…Therefore, the on-line rotor time constant estimation is inevitable to guarantee a competent performance in the IM drives. Several strategies have been proposed for rotor time constant estimation in the vector controlled IM drives [4,[6][7][8]. Among these techniques, MRAS based schemes are the most common strategies employed due to their relative simplicity and low computational effort [4,8].…”

Section: Introductionmentioning

confidence: 99%

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Study on Model Reference Fuzzy Adaptive Control for Sensorless Vector Controlled Induction Motor Drives

Jiang¹,

Ke²,

Wu³

et al. 2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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Abstract-In this paper, a model reference fuzzy adaptive system (MRFAS) control method using on-line self tuning fuzzy quantizing and scaling factors is applied to the sensorless vector controlled induction motor (IM) drive system with MRAS type speed estimator. In this method, a stator current model based MRFAS observer is presented to estimate the rotor speed and inverse rotor time constant and rotor flux is estimated using the MRAS CC estimator. A novel nonlinear adaptation mechanism is proposed in which the speed adaptation scheme and the other of inverse rotor time constant are executed by two-stage fuzzy logic controllers with self-tuned parameters based on the error and change of error measured between the actual current and the reference model output signal. Simulation results are presented to validate the effectiveness of the proposed method, showing stable system responses almost insensitive to large parameter variations.

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Section: Self-tuning Fuzzy Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study on Model Reference Fuzzy Adaptive Control for Sensorless Vector Controlled Induction Motor Drives

Jiang¹,

Ke²,

Wu³

et al. 2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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show abstract

“…The MRAS observer was used adaptive schemes based on fuzzy logic algorithm and rotor resistance estimation where derived using Lyapunov's stability theorem, taken as a parameter, and rotor resistance are much slower than that of electrical states [3,4,6]. In this paper we propose a method for estimation of the rotor constant times in an indirect rotor flux oriented controlled induction motor drive.…”

Section: Introductionmentioning

confidence: 99%

“…Among these techniques, model reference adaptive systems (MRASs) schemes are the most common strategies employed due to their relative simplicity and low computational effort [4,6]. PI controllers are widely used in industrial control systems applications.…”

Section: Introductionmentioning

confidence: 99%

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A fuzzy model reference adaptive system control for induction motor drives

Amrane

Louri

Larabi

et al. 2013

3rd International Conference on Systems and Control

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In this article, we introduce the development of a robust control adaptive system for an induction motor drives and fuzzy logic adapter to the rotor time constant estimation is proposed. We develop and combine the model reference adaptive system (MRAS) method with fuzzy logic approach to achieve our objectives. Two main objectives are covered; the first aim is to study and develop a speed control of the induction machine using the MRAS to estimate the rotor time constant, the second one is to study and develop an intelligent adaptation method based on the fuzzy logic algorithms, keeping the same performance. A robust vector control of induction motor drives scheme is proposed taking into consideration the compensation of the rotor time constant inverse variation. The new presented approach improves the performances of the MRAS compared to the usual methods. Finally, the validity of the proposed control is demonstrated by a series of computer simulations and the obtained results show that the designed control system can achieve satisfactory performances and to the adaptability of the rotor time constant variation. Index Terms --Asynchronous machine, adaptive control, fuzzy systems, estimation of the rotor time constant, model reference adaptive system (MRAS).

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Diagnostic of Sensors for Induction Machine Powered by Photovoltaic Generator Based on Fuzzy Logic Techniques

Amrane¹,

Larabi²,

Hamzaoui³

2016

Energy, Transportation and Global Warming

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Robust speed sensorless fuzzy control of the induction machine drive with adaptation of the rotor time constant supplied by photovoltaic solar energy

Cited by 3 publications

References 9 publications

Study on Model Reference Fuzzy Adaptive Control for Sensorless Vector Controlled Induction Motor Drives

Study on Model Reference Fuzzy Adaptive Control for Sensorless Vector Controlled Induction Motor Drives

A fuzzy model reference adaptive system control for induction motor drives

Diagnostic of Sensors for Induction Machine Powered by Photovoltaic Generator Based on Fuzzy Logic Techniques

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