Open AccessA High Performance Kinetic Gas Molecule Optimization (KGMO) Based ADPLL for Induction Motors Control Applications
Author(s) -
Mr. Rajat Kumar Dwibedi,
Dr.E. Logashanmugam*
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1628.039520
Subject(s) - control theory (sociology) , induction motor , torque , digital control , control engineering , computer science , mean squared error , controller (irrigation) , engineering , voltage , electronic engineering , control (management) , mathematics , artificial intelligence , agronomy , statistics , physics , biology , electrical engineering , thermodynamics
Nowadays control applications play a major role in different applications such as industrial automation, robotics, automobiles, power systems etc. The all-digital phase-locked loop (ADPLL) is a digital controller can be used commonly for all kind of control applications based on the application requirement. In the work, KGMO based ADPLL is proposed to perform the rotation control of an induction motor (KGMO-ADPLL-IMSC) under various load conditions by the varying current. The proposed ADPLL is tested in an induction motor (IM) to control the rotation of the motor under certain load conditions. Various parameters such as speed, torque, phase, amplitude and offset values are considered to generate the control signal. Root mean square error (RMSE) is considered as the objective function for the KGMO algorithm. Least error is considered for the best fitness function for the better performance. In this work, the current control technique is used to perform the rotation control of the induction motor. Various performance such as torque, speed and stability are measured under various load conditions. KGMO-ADPLL-IMSC design is implemented in an integrated MATLAB/SIMULINK environment under various inbuild and custom libraries. Experiments show that the KGMO-ADPLL-IMSC strategy is altogether improved the performance in terms of all performance evaluation graphs.