Direct Torque Control of Induction Motor Using Enhanced Firefly Algorithm — ANFIS

Abstract

In this paper, the hybrid direct torque control (DTC) technique is proposed for controlling the speed of the induction motor (IM). The hybrid technique is the combination of an enhanced firefly algorithm (FA) and the adaptive neuro fuzzy inference system (ANFIS) technique. The performance of the FA is improved by updating the randomized parameter. Here, the genetic algorithm (GA) is utilized for updating the parameter and improved the performance of the FA. Initially, the actual torque and the change of toque are applied to the input of the enhanced FA and form the electromagnetic torque as a dataset. The output of the enhanced FA is given to the input of the ANFIS which is determined from the output of interference system. The dynamic behavior of the IM is analyzed in terms of the parameters such as the speed, torque, flux, etc. Based on the parameters, the motor speed is controlled by utilizing the proposed technique. Then the output of the ANFIS is translated into the stator voltage which is given to the input of the support vector machine (SVM). After that, the control signal is generated for controlling the speed of the IM. The proposed hybrid technique is implemented in the Matlab/Simulink platform. The performance analysis of the proposed method is demonstrated and contrasted with the existing techniques such as without controller, particle swarm optimization (PSO)-based ANFIS and FA-ANFIS controller.

Slip-Ring Induction Motor Torque and Current Ripple Minimization Using Bang-Bang Current Control

“…Equations ( 1) -(3) describe the switching characteristics for the three-phase bridge VSI. One should notice that the transistor does not necessarily turn on when it is commanded to conduct; the transistor operates only if the on-switching command is provided, and the current direction corresponds to the characteristics of the transistor [17][18][19][20] .…”

ANN-based direct torque control scheme of an IM drive for a wide range of speed operation

“…Compared to the traditional PI controller and sliding stage control, this strategy provides decreased torque ripple and current distortion along with robust dynamic behaviour. In [10], the cuckoo search algorithm to train the data and test the ANFIS (adaptive neuro fuzzy inference system) to offer appropriate electromagnetic torque which thus alters the switching state of the inverter. The CS-based (current source) ANFIS speed controller performance has been compared with PI, fuzzy, and ANFIS speed controllers.…”