Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.

One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manip...

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Main Authors: Sulaiman, Nasri, Piltan, Farzin, Tajpaykar, Zahra, Ferdosali, Payman, Rashidi, Mehdi
Format: Article
Language:English
Published: 2011
Online Access:http://psasir.upm.edu.my/id/eprint/23392/
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spelling my.upm.eprints.233922014-09-09T06:34:18Z http://psasir.upm.edu.my/id/eprint/23392/ Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain. Sulaiman, Nasri Piltan, Farzin Tajpaykar, Zahra Ferdosali, Payman Rashidi, Mehdi One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Sliding mode controller (SMC) and computed torque controller (CTC) are the best nonlinear robust controllers which can be used in uncertainty nonlinear. Sliding mode controller has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non-classical method (e.g., Fuzzy Logic) in robust classical method (e.g., Sliding Mode Controller and computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani’s error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic in SMC and CTC. Second target focuses on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller and computed torque like controller by optimization the tunable gain. Therefore fuzzy sliding mode controller with tunable gain (GTFSMC) and computed torque like controller with tunable gain (GTCTLC) will be presented in this paper. 2011 Article PeerReviewed Sulaiman, Nasri and Piltan, Farzin and Tajpaykar, Zahra and Ferdosali, Payman and Rashidi, Mehdi (2011) Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain. International Journal of Robotics and Automation, 2 (3). pp. 195-210. ISSN 2180-1312 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Sliding mode controller (SMC) and computed torque controller (CTC) are the best nonlinear robust controllers which can be used in uncertainty nonlinear. Sliding mode controller has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non-classical method (e.g., Fuzzy Logic) in robust classical method (e.g., Sliding Mode Controller and computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani’s error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic in SMC and CTC. Second target focuses on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller and computed torque like controller by optimization the tunable gain. Therefore fuzzy sliding mode controller with tunable gain (GTFSMC) and computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.
format Article
author Sulaiman, Nasri
Piltan, Farzin
Tajpaykar, Zahra
Ferdosali, Payman
Rashidi, Mehdi
spellingShingle Sulaiman, Nasri
Piltan, Farzin
Tajpaykar, Zahra
Ferdosali, Payman
Rashidi, Mehdi
Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
author_facet Sulaiman, Nasri
Piltan, Farzin
Tajpaykar, Zahra
Ferdosali, Payman
Rashidi, Mehdi
author_sort Sulaiman, Nasri
title Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
title_short Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
title_full Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
title_fullStr Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
title_full_unstemmed Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC With Tunable Gain.
title_sort design artificial nonlinear robust controller based on ctlc and fsmc with tunable gain.
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/23392/
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score 13.160551