Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling i...

Full description

Saved in:
Bibliographic Details
Main Authors: Bature, A. A., Buyamin, S., Ahmad, M. N., Muhammad, M., Abdullahi, A. M.
Format: Article
Language:English
Published: Penerbit UTM Press 2016
Subjects:
Online Access:http://eprints.utm.my/id/eprint/71192/1/AmirABature2016_IntelligentControllersForVelocityTrackingofTwo.pdf
http://eprints.utm.my/id/eprint/71192/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976412209&doi=10.11113%2fjt.v78.9174&partnerID=40&md5=4408c6914a2ca2b046815320a9f196b7
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
Language: English
id my.utm.71192
record_format eprints
spelling my.utm.711922017-11-15T04:35:41Z http://eprints.utm.my/id/eprint/71192/ Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot Bature, A. A. Buyamin, S. Ahmad, M. N. Muhammad, M. Abdullahi, A. M. TK Electrical engineering. Electronics Nuclear engineering Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy. Penerbit UTM Press 2016 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/71192/1/AmirABature2016_IntelligentControllersForVelocityTrackingofTwo.pdf Bature, A. A. and Buyamin, S. and Ahmad, M. N. and Muhammad, M. and Abdullahi, A. M. (2016) Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot. Jurnal Teknologi, 78 (6-11). pp. 1-7. ISSN 0127-9696 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976412209&doi=10.11113%2fjt.v78.9174&partnerID=40&md5=4408c6914a2ca2b046815320a9f196b7
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Bature, A. A.
Buyamin, S.
Ahmad, M. N.
Muhammad, M.
Abdullahi, A. M.
Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
description Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy.
format Article
author Bature, A. A.
Buyamin, S.
Ahmad, M. N.
Muhammad, M.
Abdullahi, A. M.
author_facet Bature, A. A.
Buyamin, S.
Ahmad, M. N.
Muhammad, M.
Abdullahi, A. M.
author_sort Bature, A. A.
title Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
title_short Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
title_full Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
title_fullStr Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
title_full_unstemmed Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
title_sort intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
publisher Penerbit UTM Press
publishDate 2016
url http://eprints.utm.my/id/eprint/71192/1/AmirABature2016_IntelligentControllersForVelocityTrackingofTwo.pdf
http://eprints.utm.my/id/eprint/71192/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976412209&doi=10.11113%2fjt.v78.9174&partnerID=40&md5=4408c6914a2ca2b046815320a9f196b7
_version_ 1643656130667216896