International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Simulation and Modeling of 6-DOF Robot Manipulator Using Matlab Software

Abstract

Mechanical robotic arms have been developing in a substantially complete manner in recent years. Robotic arms can support people in remote areas or in various regions where access is limited to move objects easily and perform things with high speed and precision. A robotic arm is basically a mechanical arm which is programmable with performance same as a human arm. Robotic arms can be a part or total mechanism of a complex robot. Robotic hands are capable of doing any work that is required in designs such as painting, welding an object and so on. For example, robotic arms are doing a variety of tasks such as drilling, nut tightening of   rotating parts and spare parts in the assembly lines of    car factories. The purpose of this paper is design of a robotic arm with 6 DOF and motion simulation using a MATLAB software code and Simulink modeling. The equations of position, angles and paths are being controlled using a GUI interface. By the slider controls in the coding position angle and path of motion range will be displayed and path traces are drawn by tracking the arm movements in 3D-space using a system block of individual joints in the diagram of Simulink environment.

Country : India

1 Thavamani.P2 Ramesh.K3 Sundari.B

  1. M.E Scholar, Applied Electronics, JCET, Dharmapuri, Tamilnadu, India
  2. Associate Professor, Dept. of ECE, JCET, Dharmapuri, Tamilnadu, India
  3. Assistant Professor, Dept. of ECE, JCET, Dharmapuri, Tamilnadu, India

IRJIET, Volume 2, Issue 4, June 2018 pp. 6-10

Full Paper
Download

References

  1. S.G. Anavatti, S.A. Salman and J.Y. Choi, “Fuzzy + PID Controller for Robot Manipulator,” International Conference on Computational Intelligence for Modelling Control and Automation. pp. 75, Dec. 2006.
  2. Shiuh-Jer, H. and L. Ji-Shin.”A stable self-organizing fuzzy controller for robotic motion control." Industrial Electronics, IEEE Transactions on 47(2): 421-428, 2000.
  3. Kiam Heong, A. "PID control system analysis, design, and technology." Control Systems Technology, IEEE Transactions on 13(4): 559-576, 2005.
  4. Visioli, “Tuning of PID Controllers with Fuzzy Logic,” IEEE Proceedings Control Theory and Applications, Vol. 148, No. 1, pp. 1-8, 2001.
  5. Perry, T. S. "Lotfi A. Zadeh [fuzzy logic inventor biography]." Spectrum, IEEE 32(6): 32-35, 1995.
  6. E.H. Mamdani, “Applications of fuzzy logic to approximate reasoning using linguistic synthesis,” IEEE Transactions on Computers, Vol. 26, No. 12, pp. 1182–1191, Dec. 1977.
  7. Z.-Y. Zhao, M. Tomizuka and S. Isaka, “Fuzzy Gain Scheduling PID Controller,” IEEE Transactions on Systems, Man., Cybernetics Society, Vol. 23, No. 5, pp.1392–1398, Sep/Oct. 1993.
  8. R.P. Copeland and K.S. Rattan, “A Fuzzy Logic Supervisor for PID Control of Unknown Systems,” IEEE International Symposium on Intelligent Control., pp.22–26, Aug.1994.
  9. W. Li, "Design of a Hybrid Fuzzy Logic Proportional plus Conventional Integral Derivative Controller", IEEE Transaction on Fuzzy Systems, Vo1. 6, No. 4, pp.449–463, Nov 1998.
  10. SerdarKucuk and ZaferBingul (2006). Robot Kinematics: Forward and Inverse Kinematics, Industrial Robotics: Theory, Modelling and Control, Sam Cubero (Ed.), ISBN: 3-86611-285-8, InTech,
  11. Denavit, J. & Hartenberg, R. S. (1955). A kinematic notation for lower-pair mechanisms based on matrices”, Journal of Applied Mechanics, Vol., 1, pp. 215-221, June 1955. 

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies