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Reseach Article

Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot

by Mohammed Elsayed, Abdallah Hammad, Ashraf Hafez, Hala Mansour
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 11
Year of Publication: 2017
Authors: Mohammed Elsayed, Abdallah Hammad, Ashraf Hafez, Hala Mansour
10.5120/ijca2017914540

Mohammed Elsayed, Abdallah Hammad, Ashraf Hafez, Hala Mansour . Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot. International Journal of Computer Applications. 168, 11 ( Jun 2017), 1-6. DOI=10.5120/ijca2017914540

@article{ 10.5120/ijca2017914540,
author = { Mohammed Elsayed, Abdallah Hammad, Ashraf Hafez, Hala Mansour },
title = { Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 11 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number11/27916-2017914540/ },
doi = { 10.5120/ijca2017914540 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:15:49.965394+05:30
%A Mohammed Elsayed
%A Abdallah Hammad
%A Ashraf Hafez
%A Hala Mansour
%T Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 11
%P 1-6
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An important issue in robotics research is path tracking control where the robot is required to follow a certain path. The error between the desired path and the actual path is to converge to zero. This problem is more complicated when the robot dynamics is considered. This paper proposes a real time trajectory tracking control for a differential drive wheeled mobile robot (DDWMR) in obstacle-free environment. The robot is guided to follow certain reference path with a pre-calculated velocity profile. The controller design and analysis of the system stability are guaranteed using Lyapunov stability theory. The dynamic model of real DDWMR is derived and used in the LabVIEW simulation environment for testing the validity of designed controller. The obtained simulation results illustrate the success of the proposed controller. Also to Test the effectiveness of proposed controller, a comparison study with a widely used backstepping based controller is performed.

References
  1. G. Yuan, S. Yang, and G. Mittal, Tracking control of a mobile robot using a neural dynamics based approach, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).
  2. T. Dierks and S. Jagannathan, Control of Nonholonomic Mobile Robot Formations: Backstepping Kinematics into Dynamics, 2007 IEEE International Conference on Control Applications, 2007.
  3. I. Benaoumeur, B. Laredj, H. E. A. Reda, and A.-F. Zoubir, Backstepping Approach for Autonomous Mobile Robot Trajectory Tracking, Indonesian Journal of Electrical Engineering and Computer Science, vol. 2, no. 3, p. 478, Jan. 2016.
  4. D.-H. Kim and J.-H. Oh, Tracking control of a two-wheeled mobile robot using inputoutput linearization, Control Engineering Practice, vol. 7, no. 3, pp. 369373, 1999.
  5. J.-M. Yang and J.-H. Kim, Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots, IEEE Transactions on Robotics and Automation, vol. 15, no. 3, pp. 578587, 1999.
  6. A. Ollero, A. G. Cerezo, and J. V. Martinez, Fuzzy supervisory path tracking of mobile robots, Control Engineering Practice, vol. 2, no. 1, p. 160, 1994.
  7. A. Pandey and D. R. Parhi, Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm, Defence Technology, vol. 13, no. 1, pp. 4758, 2017.
  8. J. Velagic, N. Osmic, and B. Lacevic, Design of Neural Network Mobile Robot Motion Controller, New Trends in Technologies, Jan. 2010.
  9. M. K. Singh and D. R. Parhi, Intelligent neuro-controller for navigation of mobile robot, Proceedings of the International Conference on Advances in Computing, Communication and Control - ICAC3 09, 2009. Vol. 4 No. 1 2012 ISSN: 0975- 3176 pp. 19-26
  10. Y. Tian and N. Sarkar, Control of a Mobile Robot Subject to Wheel Slip, Journal of Intelligent and Robotic Systems, vol. 74, no. 3-4, pp. 915929, Sep. 2013.
  11. N. Sarkar, X. Yun, and V. Kumar, Control of Mechanical Systems With Rolling Constraints, The International Journal of Robotics Research, vol. 13, no. 1, pp. 5569, 1994.
  12. R. Fierro and F. Lewis, Control of a nonholonomic mobile robot: backstepping kinematics into dynamics, Proceedings of 1995 34th IEEE Conference on Decision and Control.
Index Terms

Computer Science
Information Sciences

Keywords

Trajectory tracking nonholonomic robots dynamic Modeling differential drive Lyapunov stability mobile robot