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Tracking-Error Fuzzy-Based Control for Nonholonomic Wheeled Robots

Tracking-Error Fuzzy-Based Control for Nonholonomic Wheeled Robots In this paper, the trajectory to be tracked by a differentially driven wheeled mobile robot (DDWMR) is controlled. The considered DDWMR has a chassis with two active wheels and a front idle wheel. After introducing the kinematic model of the robot, the robot trajectory tracking problem using fuzzy and optimal fuzzy logic methods will be analyzed. Also, the same mission will be conducted using model predictive control (MPC) method. Minimizing the path tracking error is the objective of the controllers design. Moreover, the velocity and acceleration constraints are included in the proposed controllers design procedure to prevent the DDWMR from slipping and path curvature deviation. Finally, tracking error results for fuzzy, optimal fuzzy and model predictive controllers are compared. The tracking error analysis of the obtained simulation results, in MATLAB software, reveals the better performance of the designed fuzzy controller (FC) over the MPC, and the better performance of the designed optimal fuzzy controller over the FC. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Arabian Journal for Science and Engineering Springer Journals

Tracking-Error Fuzzy-Based Control for Nonholonomic Wheeled Robots

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References (27)

Publisher
Springer Journals
Copyright
Copyright © 2018 by King Fahd University of Petroleum & Minerals
Subject
Engineering; Engineering, general; Science, Humanities and Social Sciences, multidisciplinary
ISSN
1319-8025
eISSN
2191-4281
DOI
10.1007/s13369-018-3336-6
Publisher site
See Article on Publisher Site

Abstract

In this paper, the trajectory to be tracked by a differentially driven wheeled mobile robot (DDWMR) is controlled. The considered DDWMR has a chassis with two active wheels and a front idle wheel. After introducing the kinematic model of the robot, the robot trajectory tracking problem using fuzzy and optimal fuzzy logic methods will be analyzed. Also, the same mission will be conducted using model predictive control (MPC) method. Minimizing the path tracking error is the objective of the controllers design. Moreover, the velocity and acceleration constraints are included in the proposed controllers design procedure to prevent the DDWMR from slipping and path curvature deviation. Finally, tracking error results for fuzzy, optimal fuzzy and model predictive controllers are compared. The tracking error analysis of the obtained simulation results, in MATLAB software, reveals the better performance of the designed fuzzy controller (FC) over the MPC, and the better performance of the designed optimal fuzzy controller over the FC.

Journal

Arabian Journal for Science and EngineeringSpringer Journals

Published: Jun 5, 2018

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