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Permanent magnet DC motor (PMDC) model identification and controller design Cover

Permanent magnet DC motor (PMDC) model identification and controller design

By: Ahmed Alkamachi  
Open Access
|Oct 2019

Abstract

System modeling is a set of mathematical equations that describe the dynamical behavior of a system. It is considered as a primary concern in determining a suitable controller to meet specific requirements. An autoregressive with exogenous terms (ARX) model for a PMDC motor is identified experimentally based on the recursive least square (RLS) method. Adaptive discrete pole placement controller (APPC) is proposed and designed aiming to control the motor revolving speed. For the comparison purpose, a discrete Proportional Integral (PI) controller is also considered in this work. The steady step response, transient response, and the mean squared error (MSE) is counted throughout the comparison. The e ect of the uncertainties in the PMDC model is also investigated in this paper. The result shows a superiority in the performance of the proposed controller compared to that obtained using PI controller.

DOI: https://doi.org/10.2478/jee-2019-0060 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 303 - 309
Submitted on: Jul 6, 2019
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Published on: Oct 21, 2019
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2019 Ahmed Alkamachi, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.