Performance measure and analysis of speed regulation in permanent magnet synchronous motor using modified optimization techniques

Abstract

Synchronous motors are used in industrial applications with higher newlineefficiency and better performances. The Permanent Magnet Synchronous Motor newline(PMSM) is playing significant part in advanced motor drives. PMSM is a newlinesynchronous motor with permanent magnets rather than windings in rotor that newlinegenerate a constant magnetic field. PMSM gained large acceptance in motion newlinecontrol applications because of its high performance, condensed structure, high newlineair-gap flux density, large power density, high torque to inertia ratio and high newlineefficiency. PMSM technology increases the performance in variable speed newlineapplication. Speed regulation of PMSM is carried out through Proportional newlineIntegral (PI), Proportional Integral Derivative (PID) and Sliding mode controller. newlineMany research works have been carried out for enhancing the speed regulation newlineperformance using various controller techniques. newlineSliding-Mode controller eliminates the dependency of machine newlineparameters and external disturbances effect for speed control of PMSM drive newlinesystem. A nonlinear observer was employed for finding the rotor speed and load newlinetorque. The computational time was not reduced through existing speed newlinecontroller methods. The computational cost was not reduced by using designed newlineadaptive differential evolution algorithm. In addition, the unknown set of newlinecontrolling parameters failed to control the speed of PMSM. In order to address newlinethese limitations, the research work proposes two different methods, namely a newlinenovel adaptive Extreme Learning Machine (ELM) neural network based fuzzy newlinecontroller and Particle Swarm Maxpooling Fully Connective Deep Convolutional newlineNeural Learnt Sugeno-Takagi Fuzzy Controller (PSMFCDCNLSTFC) model newline