Improvement of the induction motor sensorless control based on the type-2 fuzzy logic

Benlaloui, I.; Chrifi‐Alaoui, Larbi; Ouriagli, M.; Khemis, A.; Khamari, D.; Drid, Saïd

doi:10.1007/s00202-020-01178-1

Cited by 8 publications

(9 citation statements)

References 26 publications

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“…In order to make the comparison result more intuitive, this example only intercepts the picture of the rainbow bridge model and does not add the reconstructed useless information to the comparison. It can be seen from the time comparison that this method is still applicable when the target is a large structure, which can greatly reduce the modeling time [13,14].…”

Section: D Model Construction Based On Image Processingmentioning

confidence: 99%

Image Processing Based on Fuzzy Mathematics Theory

Hou

2022

Security and Communication Networks

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In order to further improve the problems of poor rationality and weak antinoise ability of existing image processing algorithms and technical algorithms, an image processing research method based on fuzzy mathematical theory is proposed. First, aiming at the ill-posed problem of the PFCM algorithm, the neutrality and rejection degree are used to construct a regular term and embed the algorithm objective function to enhance the correlation between the attribute parameters of the fuzzy set of the sample graph, so as to solve the ill-posed problem of the PFCM algorithm. Secondly, in view of the same noise sensitivity problem of PFCM algorithm as a traditional fuzzy clustering algorithm, combined with the robust ideas of FCM_S1 and FCM_S2 algorithms, the objective function of robust segmentation algorithm for graph fuzzy clustering (RPFCM_s) is constructed. The misclassification rate of the clustering algorithm proposed in this study in image segmentation is reduced by 38%–76%, and the misclassification rate of the corresponding segmentation result of the ATPFCA algorithm is reduced by 5%–77%. Therefore, the algorithm not only improves the effective segmentation efficiency of the fuzzy mathematical theory algorithm for the processing of uneven grayscale images but also enhances the anti-noise robustness of the algorithm.

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Section: D Model Construction Based On Image Processingmentioning

confidence: 99%

Image Processing Based on Fuzzy Mathematics Theory

Hou

2022

Security and Communication Networks

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“…In Figure 5(a) the architecture and description of type-1 and in Figure 5(b) architecture and description of type-2 fuzzy system is depicted. The benefits of type-2 fuzzy logic controller (T2FLC) over type-1 fuzzy logic controller (T1FLC) are given in [22], [23]. However, dead time can be inserted as in [24] in PWM algorithms of [22], [23].…”

Section: Proposed Fuzzy Logic-based Space Vector Pwmmentioning

confidence: 99%

“…The benefits of type-2 fuzzy logic controller (T2FLC) over type-1 fuzzy logic controller (T1FLC) are given in [22], [23]. However, dead time can be inserted as in [24] in PWM algorithms of [22], [23]. The complete fuzzy computing method has background concept of fuzzy set theory [25]- [29].…”

Section: Proposed Fuzzy Logic-based Space Vector Pwmmentioning

confidence: 99%

Type-1 and type-2 fuzzy logic-based space vector modulation for two-level inverter fed induction motor

Tikkani¹,

Prasad

2022

TELKOMNIKA

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Two-level inverter control with type-1 and type-2 fuzzy logic-based space vector pulse-width modulation (PWM) method for induction motor drive (IMD) is presented in this paper. A new sampling time independent strategy with type-1 and type-2 fuzzy based methods are used in generating three phase duty ratios which are directly obtained without mathematical equations. The conventional method of space vector modulation (SVM) produces the duty ratios for the inverter which are sampling time dependent. However, in type-1 and type-2 fuzzy based space vector PWM algorithms, the three phases duty ratios generated are sampling time independent and with a new integrated dead-time insertion in SVM itself, can be implemented practically for any switching frequency. As the rule-base for Mamdani non-singleton interval type-1 and type-2 fuzzy inference systems are designed manually, with the expert knowledge of conventional space vector PWM, the duty ratios of the inverter are generated such that the performance of the IMD is improved. The simulation studies for aforementioned cases is performed in matrix laboratory (MATLAB) and experimental validation for the proposed space vector PWM algorithms is validated using real-time sacraetheologiae magister (STM) hardware with STM32F429I Cortex M4 processor for a 1 hp IMD.

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“…Various estimation techniques for the rotor speed have been suggested in the literature in order to estimate the rotor speed in a closed loop utilizing the measured stator currents and voltages, like the full-order observer, 40 the extended Kalman filter, [41][42][43] the SMO, [44][45][46][47][48] the Luenberger observer 49,50 and the model reference adaptive system (MRAS). [51][52][53][54][55][56][57][58][59][60][61] Mostly, sensorless algorithms have proved their good performance at high-and mediumspeed ranges. However, there are lacks in terms of robustness and accuracy, especially at a very low speed and a locked rotor.…”

Section: Introductionmentioning

confidence: 99%

“…42 Among the suggested speed estimation methods, the MRAS speed estimator can be considered as the most commonly utilized method thanks to its simplicity of implementation. [51][52][53][54][55][56][57][58][59][60][61] The MRAS is based on two models and an adaptation mechanism. The first one is called the reference model which consists in estimating the rotor or the stator fluxes.…”

Section: Introductionmentioning

confidence: 99%

Design and Xilinx Virtex-field-programmable gate array for hardware in the loop of sensorless second-order sliding mode control and model reference adaptive system–sliding mode observer for direct torque control of induction motor drive

Krim

Mimouni

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article aims first to propose an improved space vector modulation–direct torque control in order to enhance the induction motor performance using: (1) a super-twisting controller and (2) a novel model reference adaptive system based on a sliding mode observer. Second, due to the complexity of the suggested control algorithm, this article deals also with a hardware implementation on a field-programmable gate array board. Indeed, the field-programmable gate array is mainly chosen to reduce the execution time, thanks to its parallel processing which significantly improves the quality of the control system by reducing the sampling period, and consequently the delays in the control loop. Besides, the super-twisting controller is proposed to enhance the speed regulation loop which is a second-order sliding mode control technique that uses a continuous control law to prevent the chattering phenomenon induced by the first-order sliding mode control technique. Moreover, the high performance control requires information about the rotor speed which can be obtained by a sensor. Generally, the use of the speed sensor increases the system cost and size, and reduces its system reliability. Therefore, a combination between a model reference adaptive system observer and a sliding mode observer is suggested for speed estimation and overcoming the sensitivity of the classical model reference adaptive system observer against uncertainties and stator resistance variations. The performance of the proposed space vector modulation--direct torque control--super-twisting controller with the model reference adaptive system--sliding mode observer algorithm of an induction motor is verified through simulation, hardware co-simulation and experimental validation utilizing a field-programmable gate array Virtex-5-ML507 board. The performance of the suggested sensorless control method is compared also with other recent published schemes.

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Improvement of the induction motor sensorless control based on the type-2 fuzzy logic

Cited by 8 publications

References 26 publications

Image Processing Based on Fuzzy Mathematics Theory

Image Processing Based on Fuzzy Mathematics Theory

Type-1 and type-2 fuzzy logic-based space vector modulation for two-level inverter fed induction motor

Design and Xilinx Virtex-field-programmable gate array for hardware in the loop of sensorless second-order sliding mode control and model reference adaptive system–sliding mode observer for direct torque control of induction motor drive

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