Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator

Wahyudi, Siti Salasiah Mokri, Amir A. Shafie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Robotics is a field of modern technology which requires knowledge in vast areas such as electrical engineering, mechanical engineering, computer science as well as finance. Nonlinearities and parametric uncertainties are unavoidable problems faced in controlling robots in industrial plants. Tracking control of a single link manipulator driven by a permanent magnet brushed dc motor is a nonlinear dynamics due to effects of gravitational force, mass of the payload, posture of the manipulator and viscous friction coefficient. Furthermore uncertainties arise because of changes of the rotor resistance with temperature and random variations of friction while operating. Due to this fact classical PID controller can not be used effectively since it is developed based on linear system theory. Neural network control schemes for manipulator control problem have been proposed by researchers; in which their competency is validated through simulation studies. On the other hand, actual real time applications are rarely established. Instead of simulation studies, this paper is aimed to implement neural network controller in real time for controlling a DC motor driven single link manipulator. The work presented in this paper is concentrating on neural NARMA L2 control and its improvement called to as Smoothed NARMA L2 control. As proposed by K. S Narendra and Mukhopadhyay, Narma L2 control is one of the popular neural network architectures for prediction and control. The real time experimentation showed that the Smoothed NARMA L2 is effective for controlling the single link manipulator for both point-to-point and continuous path motion control.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development
Pages691-697
Number of pages7
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development - Kuala Lumpur
Duration: 13 May 200815 May 2008

Other

OtherInternational Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development
CityKuala Lumpur
Period13/5/0815/5/08

Fingerprint

Feedback linearization
Manipulators
Neural networks
Friction
Controllers
DC motors
Electrical engineering
System theory
Motion control
Mechanical engineering
Finance
Network architecture
Computer science
Permanent magnets
Linear systems
Industrial plants
Robotics
Rotors
Robots

ASJC Scopus subject areas

  • Computer Science Applications
  • Human-Computer Interaction

Cite this

Wahyudi, Mokri, S. S., & Shafie, A. A. (2008). Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator. In Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development (pp. 691-697). [4580693] https://doi.org/10.1109/ICCCE.2008.4580693

Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator. / Wahyudi, ; Mokri, Siti Salasiah; Shafie, Amir A.

Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. p. 691-697 4580693.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wahyudi, , Mokri, SS & Shafie, AA 2008, Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator. in Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development., 4580693, pp. 691-697, International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development, Kuala Lumpur, 13/5/08. https://doi.org/10.1109/ICCCE.2008.4580693
Wahyudi , Mokri SS, Shafie AA. Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator. In Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. p. 691-697. 4580693 https://doi.org/10.1109/ICCCE.2008.4580693
Wahyudi, ; Mokri, Siti Salasiah ; Shafie, Amir A. / Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator. Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. pp. 691-697
@inproceedings{a3a02cae215f463d98222495b07340ec,
title = "Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator",
abstract = "Robotics is a field of modern technology which requires knowledge in vast areas such as electrical engineering, mechanical engineering, computer science as well as finance. Nonlinearities and parametric uncertainties are unavoidable problems faced in controlling robots in industrial plants. Tracking control of a single link manipulator driven by a permanent magnet brushed dc motor is a nonlinear dynamics due to effects of gravitational force, mass of the payload, posture of the manipulator and viscous friction coefficient. Furthermore uncertainties arise because of changes of the rotor resistance with temperature and random variations of friction while operating. Due to this fact classical PID controller can not be used effectively since it is developed based on linear system theory. Neural network control schemes for manipulator control problem have been proposed by researchers; in which their competency is validated through simulation studies. On the other hand, actual real time applications are rarely established. Instead of simulation studies, this paper is aimed to implement neural network controller in real time for controlling a DC motor driven single link manipulator. The work presented in this paper is concentrating on neural NARMA L2 control and its improvement called to as Smoothed NARMA L2 control. As proposed by K. S Narendra and Mukhopadhyay, Narma L2 control is one of the popular neural network architectures for prediction and control. The real time experimentation showed that the Smoothed NARMA L2 is effective for controlling the single link manipulator for both point-to-point and continuous path motion control.",
author = "Wahyudi and Mokri, {Siti Salasiah} and Shafie, {Amir A.}",
year = "2008",
doi = "10.1109/ICCCE.2008.4580693",
language = "English",
isbn = "9781424416929",
pages = "691--697",
booktitle = "Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development",

}

TY - GEN

T1 - Real time implementation of NARMA L2 feedback linearization and smoothed NARMA L2 controls of a single link manipulator

AU - Wahyudi,

AU - Mokri, Siti Salasiah

AU - Shafie, Amir A.

PY - 2008

Y1 - 2008

N2 - Robotics is a field of modern technology which requires knowledge in vast areas such as electrical engineering, mechanical engineering, computer science as well as finance. Nonlinearities and parametric uncertainties are unavoidable problems faced in controlling robots in industrial plants. Tracking control of a single link manipulator driven by a permanent magnet brushed dc motor is a nonlinear dynamics due to effects of gravitational force, mass of the payload, posture of the manipulator and viscous friction coefficient. Furthermore uncertainties arise because of changes of the rotor resistance with temperature and random variations of friction while operating. Due to this fact classical PID controller can not be used effectively since it is developed based on linear system theory. Neural network control schemes for manipulator control problem have been proposed by researchers; in which their competency is validated through simulation studies. On the other hand, actual real time applications are rarely established. Instead of simulation studies, this paper is aimed to implement neural network controller in real time for controlling a DC motor driven single link manipulator. The work presented in this paper is concentrating on neural NARMA L2 control and its improvement called to as Smoothed NARMA L2 control. As proposed by K. S Narendra and Mukhopadhyay, Narma L2 control is one of the popular neural network architectures for prediction and control. The real time experimentation showed that the Smoothed NARMA L2 is effective for controlling the single link manipulator for both point-to-point and continuous path motion control.

AB - Robotics is a field of modern technology which requires knowledge in vast areas such as electrical engineering, mechanical engineering, computer science as well as finance. Nonlinearities and parametric uncertainties are unavoidable problems faced in controlling robots in industrial plants. Tracking control of a single link manipulator driven by a permanent magnet brushed dc motor is a nonlinear dynamics due to effects of gravitational force, mass of the payload, posture of the manipulator and viscous friction coefficient. Furthermore uncertainties arise because of changes of the rotor resistance with temperature and random variations of friction while operating. Due to this fact classical PID controller can not be used effectively since it is developed based on linear system theory. Neural network control schemes for manipulator control problem have been proposed by researchers; in which their competency is validated through simulation studies. On the other hand, actual real time applications are rarely established. Instead of simulation studies, this paper is aimed to implement neural network controller in real time for controlling a DC motor driven single link manipulator. The work presented in this paper is concentrating on neural NARMA L2 control and its improvement called to as Smoothed NARMA L2 control. As proposed by K. S Narendra and Mukhopadhyay, Narma L2 control is one of the popular neural network architectures for prediction and control. The real time experimentation showed that the Smoothed NARMA L2 is effective for controlling the single link manipulator for both point-to-point and continuous path motion control.

UR - http://www.scopus.com/inward/record.url?scp=51849161945&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51849161945&partnerID=8YFLogxK

U2 - 10.1109/ICCCE.2008.4580693

DO - 10.1109/ICCCE.2008.4580693

M3 - Conference contribution

AN - SCOPUS:51849161945

SN - 9781424416929

SP - 691

EP - 697

BT - Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development

ER -