Work

Experimental dataset to develop a parametric model based of DC geared motor in feeder machine

Year: 2019

Type: article

Abstract: This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC Geared motor in feeder machine. The experimental was conducted to measure the input (voltage) and output (speed) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is Time, Man Square Error (MSE) and Average Time. One of the best model has been chosen based on the optimum parameters.

Source: International Journal of Electrical and Computer Engineering (IJECE)

DOI: 10.11591/ijece.v9i3.pp1576-1584

Authors: Azlan. W. M., Salleh S. M., Mahzan S, Sadikin A, Ahmad S

Institution: Tun Hussein Onn University of Malaysia

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Universiti Tun Hussein Onn Malaysia