Data Research, Vol. 4, Issue 6, Dec  2020, Pages 9-19; DOI: https://doi.org/10.31058/j.data.2020.46002 https://doi.org/10.31058/j.data.2020.46002

PUMA Robot Dynamics Control System with Three Dimensional Approaches Using MATLAB/ SIMULINK

, Vol. 4, Issue 6, Dec  2020, Pages 9-19.

DOI: https://doi.org/10.31058/j.data.2020.46002

Htet Htet Lin Zaw 1* , Su Mon Aye 2 , Aye Than Mon 3 , Phyoe Sandar Win 2 , Khaing Wai Pyone 3

1 Department of Electronic Engineering, Technological University (Pathein), Pathein, Myanmar

2 Department of Electronic Engineering, Technological University (Myeik), Myeik, Myanmar

3 Department of Electronic Engineering, Technological University (Loikaw), Loikaw, Myanmar

Received: 1 June 2020; Accepted: 24 September 2020; Published: 12 October 2020

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Abstract

The paper focuses to Implementation of 3D of PUMA Robot Dynamic Control System Using SIMULINK. In this Thesis to be the same real system and mathematical model of dynamics used the control system design, fine-tuning of controller is always needed. For better tuning fast simulation speed is desired. Since, Matlab incorporates LAPACK to increase the speed and complexity of matrix computation, dynamics, forward and inverse kinematics of PUMA Robot is modeled on Matlab/Simulink in such a way that all operations are matrix based which give very less simulation time. This paper compares PID parameter tuning using Genetic Algorithm, Simulated Annealing, Generalized Pattern Search (GPS) and Hybrid Search techniques. This system is implemented with MATLAB programming language.

Keywords

PUMA Robot, Robot Dynamics Control System, MATLAB, SIMULINK, Stability Analysis

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

References

[1] Kurfess, T.R. Robotics and automation handbook: CRC, 2005.

[2] Slotine, J.J.E.; Li, W. Applied nonlinear control vol. 461: Prentice hall Englewood Cliffs, NJ, 1991.

[3] Ogata, K. Modern control engineering: Prentice Hall, 2009.

[4] Cheng, L. et al. Multi-agent based adaptive consensus control for multiple manipulators with kinematic uncertainties. 2008; pp. 189-194.

[5] DAzzo, J.J. et al., Linear control system analysis and design with MATLAB: CRC, 2003.

[6] Sicilian, B.; Khatib, O. Springer handbook of robotics: Springer-Verlag New York Inc, 2008.

[7] Brian, A.; Oussama, K.; Joel, B. The Explicit Dynamic Model and Inertial Parameters of the PUMA 560 Arm. Stanford University, Artificial Intelligence Laboratory, IEEE 1986.

[8] Abdel-Razzak MERHEB. Nonlinear Control Algorithms applied to 3 DOF PUMA Robot. METU 2008.

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