Repetitive Learning Controller for Six Degree of Freedom Robot Manipulator


(*) Corresponding author


Authors' affiliations


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


In this paper a repetitive learning control of robot manipulator is presented. The trajectory tracking performance and control of the robot manipulator is studied by applying the controller. The validity of the above controller is shown by the simulation results of six degree of freedom robot manipulator. Simulation results are also compared with the existing conventional controller such as PD, computed torque and decentralized controller. Finally it is concluded that the proposed controller produce superior trajectory tracking performance and minimized trajectory tracking error.
Copyright © 2013 Praise Worthy Prize - All rights reserved.

Keywords


PUMA Manipulator; Repetitive Learning Control; Computed Torque Control; PD Control; Decentralised Adaptive Control

Full Text:

PDF


References


Spong .M.Vidyasagar. Robot dynamics and control Wiley, New York.(1989)

T. Das, C. Dülger, Mathematical modeling, simulation and experimental verification of a SCARA robot, Simulation Modelling Practice and Theory 13(2005)257-271.

S.Mohan, S.Bhanot .Comparative study of some adaptive fuzzy algorithms for manipulator control. International Journal of Computational Intelligence2006;3(4):30311.

R. Kelly , R. Carelli,A class of nonlinear PD-type controllers for robotic manipulators. Journal of Robotic Systems, 13(12): 793--802, 1996.

Y. L. Sun , M. J. Er, Hybrid fuzzy control of robotics systems, IEEE Transactions on Fuzzy Systems, vol. 12, no. 6, pp.755–765, 2004.

C.-M. Lin , Y.-J. Mon, “Hybrid adaptive fuzzy controllers with application to robotic systems, Fuzzy Sets and Systems, vol. 139, no. 1, pp. 151–165, 2003.

S. Mohan , S. Bhanot, Comparative study of some adaptive fuzzy algorithms for manipulator control, International Journal of Computational Intelligence, vol. 3, no. 4, pp. 303–311, 2006.

J. Zhou , P. Coiffet, Fuzzy control of robots, in Proceedings of IEEE International Conference on Fuzzy Systems, pp. 1357–1364, San Diego, Calif, USA, March 1992.

D.M.Adhyaru,J.Patel , R.Gianchandai , Adaptive Neuro-Fuzzy Inference System based control of robotic manipulators International conference on Mechanical and electrical technology(ICMET),Instrumentation and control Eng., Dept., Nirma Univ., Ahmedabad, India .pp 353-358.

Ouamri Bachir , Ahmed-foitih Zoubir ,Adaptive Neuro-fuzzy Inference System Based Control of Puma 600 Robot Manipulator, International Journal of Electrical and Computer Engineering (IJECE)Vol.2, No.1, February 2012, pp. 90-97.

Srinivasan Alavandar , M.J. Nigam ,New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties Comparative study,ISA Transactions 48 (2009)497-502.

Serhan Yamacli , Huseyin Canbolat ,Simulation of a SCARA robot with PD and learning controllers”. Simulation Modelling Practice and Theory ,16 (2008) 1477–1487.

W. Messner, R. Horowitz, W.W. Kao, M. Boals, A new adaptive learning rule, IEEE Transactions on Automatic Control 36 (1991) 188–197.

H. Ug˘uz, H. Canbolat, Simulation of a hybrid adaptive–learning control law for a rigid link electrically driven robot manipulator, Robotica 24 (2006) 349–354.

Wu Yilei, Song Qing, Yang Xulei, Robust recurrent neural network control of biped robot. Journal of Intelligent and Robotic Systems 2007;49(2):151-69.

Teixeira RoselitoA, Braga AntoNioDeP, De Menezes Benjamim.R,Control of a robotic manipulator using artificial neural networks with on-line adaptation.Neural Processing Letters 2000;12:19-31.

corke Peter I,The unimation puma servo system. Australia: CSIRO Division of manufacturing Technology; July 1994.

Song Z, Yi J, Zhao D, Li X, A computed torque controller for uncertain robotic manipulator systems: Fuzzy approach. Fuzzy Sets and Systems 2005;154(2):208-26.

Armstrong Brian, Khatib Oussama, Burdick Joel, The explicit dynamic model and inertial parameters of the PUMA 560 Arm, Stanford Artificial Intelligence Laboratory Stanford University. IEEE Transactions and Systems 1986,

S. W. Nawawi, M. N. Ahmad, J. H. S. Osman, Nonlinear Control Technique for a Class of Wheeled Mobile Robot, (2008) International Review of Automatic Control (IREACO), 1 (4), pp. 528-542.

A. Sakly, A. Azzouna, A. Trimeche, A. Mtibaa, PD-like and PI-like Fuzzy Control Implementation using FPGA Technology, (2011) International Review of Automatic Control (IREACO), 4 (1), pp. 65-77.

R. Prakash, R. Anita, Design of Model Reference Adaptive Intelligent Controller using Neural Network for Nonlinear Systems, (2011) International Review of Automatic Control (IREACO), 4 (2), pp. 153-161.

Noshadi, A., Mailah, M., Fuzzy-based active force with computed torque control of 3-RRR parallel robotic manipulator, (2011) International Review on Modelling and Simulations (IREMOS), 4 (5), pp. 2666-2676.


Refbacks

  • There are currently no refbacks.


Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize