V/f-Based Speed Controllers for an Induction Motor Using AI Techniques: A Comparative Analysis

Gupta, Awadhesh; Mathew, Lini; Chatterji, S.

doi:10.1007/978-81-322-1602-5_122

Cited by 1 publication

(2 citation statements)

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“…An improved hybrid control system involves an optimization control method, and ANFIS is used to adjust the M of the reference signal to increase speed accuracy and improve the motor's performance. The results have been carried out for two loads (TL) 10 N.m and 20 N.m, and different values of speeds from 1000 r.p.m to 2000 r.p.m using three types of controllers: classical PI controller, optimization method controller, and ANFIS-Optimization controller; the ratings of the motor parameters are shown in Table 1 [15].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In order to improve the output voltage of the inverter and reduce the THD, the switches used in the inverter are driven by a PWM technique. In this research, three-speed control methods are used to control the modulation factor of PWM technology: the traditional method, the optimization method, and the hybrid ANFIS-Optimization method and by controlling the value of M [14,15].…”

Section: Variable Frequency Drivementioning

confidence: 99%

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An Intelligent Hybrid Control System using ANFIS-Optimization for Scalar Control of an Induction Motor

Mohammed,

Alsammak

2023

JESA

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Recently, the three-phase induction motor (IM) has been widely used in AC motor drives and in industrial applications. The IM suffers from the accuracy of controlling the speed when it operates at different loads; this problem attracts the attention of many researchers in this field. This paper presents an Intelligent Hybrid Control System using ANFIS (Adaptive Neuro-Fuzzy Inference System)-Optimization for Scalar Control (SC) of an Induction Motor. In order to obtain optimum performance of the motor and to decrease the Total Harmonics Distortion (THD) of the motor current a Voltage Source Inverter (VSI) based on the Pulse Width Modulation technique (PWM) is used to drive the motor. To improve the speed response, accuracy and the motor's performance, an improved hybrid control system involves an optimization control method in addition to an Adaptive Neuro-Fuzzy Inference System used to adjust the amplitude and the Modulation Index (MI) of the reference signal. The proposed hybrid system improves the transient stability of motor speed and reaches a steady state much faster than the traditional controller. The Matlab-Simulink results proved the remarkable effectiveness of the proposed controller when comparing the results with two other controllers, the usual PI controller and the optimization controller.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Variable Frequency Drivementioning

confidence: 99%