Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

INTEGRATION OF PARTICLE SWARM OPTIMIZATION (PSO) TECHNIQUE INTO DC MOTOR CONTROL

NORDIN, NATHASYA NADJWA (2011) INTEGRATION OF PARTICLE SWARM OPTIMIZATION (PSO) TECHNIQUE INTO DC MOTOR CONTROL. Universiti Teknologi PETRONAS. (Unpublished)

[img] PDF
Download (2252Kb)

Abstract

Particle Swarm Optimization (PSO), an artificial method to determine the optimal proportional- integral- derivative (PID) controller parameters to be integrated into a brushed DC motor is presented. Particle Swarm Optimization (PSO), developed by Eberhart and Kennedy in 1995 was inspired by swarming patterns occurring in nature such as flocking birds. It was observed that each individual exchanges previous experience, hence knowledge of the "best position" attained by an individual becomes globally known. In the study, the problem of identifying the PID controller parameters is considered as an optimization problem. An attempt has been made to determine the PID parameters employing the PSO technique. This technique is used to improve the step response of a second order system. The step response of the given system is defined in rise time, settling time and peak overshoot. The best parameters to be used for PSO that can optimize the performance of a DC Motor (e.g.: population size, acceleration constant and inertia weight factor) is evaluated. First chapter discusses the types of DC motor available in industry nowadays and the origination of Particle Swarm Optimization technique itself. Next, the following chapter continues with the implementation of DC motor control and the tuning available that has been researched before. The usage of Particle Swarm Optimization technique is briefly explained which comprises the 6-steps of selection process. For this study, the software used is MATLAB/Simulink, where the implementation of the chosen DC motor model is represented and Particle Swarm Optimization is integrated into the PID controller of the motor, to observe the performance of chosen parameters. The results of PID controller tuning and also the results for the implementation ofPSO based PID controller is presented on the Result & Discussion chapter. Comparison then is made and discussed to see whether the results are as expected. Lastly, recommendation and conclusion pertaining to the completion of this project is presented.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Power Electronics - Power Electronics - Control Devices
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 13 Nov 2013 15:18
Last Modified: 25 Jan 2017 09:41
URI: http://utpedia.utp.edu.my/id/eprint/10516

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...