Hierarchical Fuzzy Sliding-Mode Adaptive Control for the Trajectory Tracking of Differential-Driven Mobile Robots

Hsiu Ming Wu, Mansour Karkoub

Research output: Contribution to journalArticle

Abstract

The trajectory tracking of a differential-driven mobile robot (DDMR) with uncertainties and unknown dynamics is investigated using a hierarchical fuzzy sliding-mode adaptive controller (HFSMAC). First, the position error between the actual DDMR and the virtual reference DDMR with respect to the world frame is determined. Based on the aforementioned position error, fuzzy sliding-mode control is used to generate the virtual reference input and attain position tracking. It is well known that the performance and stability of a closed-loop system often deteriorate in the presence of uncertainties. Therefore, a function approximation technique (FAT)-based adaptive controller is used here to learn the unknown dynamics and deals with the external uncertainties via a set of Fourier series to achieve velocity tracking. The proposed HFSMAC has been verified to lead to good robustness levels, effective learning, and accurate trajectory tracking. Computer simulations have been conducted to validate the theoretical developments confirming the efficacy and robustness of the proposed scheme. Finally, a comparative study with a PID controller is presented to further prove the superior performance of the proposed HFSMAC.

Original languageEnglish
Pages (from-to)33-49
Number of pages17
JournalInternational Journal of Fuzzy Systems
Volume21
Issue number1
DOIs
Publication statusPublished - 6 Feb 2019

Fingerprint

Adaptive Sliding Mode Control
Trajectory Tracking
Mobile Robot
Mobile robots
Sliding Mode
Trajectories
Controller
Controllers
Uncertainty
Fuzzy Sliding Mode Control
Robustness
Unknown
PID Controller
Function Approximation
Fourier series
Closed-loop System
Comparative Study
Efficacy
Sliding mode control
Fuzzy control

Keywords

  • Differential-driven mobile robot
  • Function approximation technique
  • Hierarchical fuzzy sliding-mode adaptive control
  • Lyapunov stability criteria
  • Virtual reference input

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

Cite this

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title = "Hierarchical Fuzzy Sliding-Mode Adaptive Control for the Trajectory Tracking of Differential-Driven Mobile Robots",
abstract = "The trajectory tracking of a differential-driven mobile robot (DDMR) with uncertainties and unknown dynamics is investigated using a hierarchical fuzzy sliding-mode adaptive controller (HFSMAC). First, the position error between the actual DDMR and the virtual reference DDMR with respect to the world frame is determined. Based on the aforementioned position error, fuzzy sliding-mode control is used to generate the virtual reference input and attain position tracking. It is well known that the performance and stability of a closed-loop system often deteriorate in the presence of uncertainties. Therefore, a function approximation technique (FAT)-based adaptive controller is used here to learn the unknown dynamics and deals with the external uncertainties via a set of Fourier series to achieve velocity tracking. The proposed HFSMAC has been verified to lead to good robustness levels, effective learning, and accurate trajectory tracking. Computer simulations have been conducted to validate the theoretical developments confirming the efficacy and robustness of the proposed scheme. Finally, a comparative study with a PID controller is presented to further prove the superior performance of the proposed HFSMAC.",
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author = "Wu, {Hsiu Ming} and Mansour Karkoub",
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AU - Karkoub, Mansour

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Y1 - 2019/2/6

N2 - The trajectory tracking of a differential-driven mobile robot (DDMR) with uncertainties and unknown dynamics is investigated using a hierarchical fuzzy sliding-mode adaptive controller (HFSMAC). First, the position error between the actual DDMR and the virtual reference DDMR with respect to the world frame is determined. Based on the aforementioned position error, fuzzy sliding-mode control is used to generate the virtual reference input and attain position tracking. It is well known that the performance and stability of a closed-loop system often deteriorate in the presence of uncertainties. Therefore, a function approximation technique (FAT)-based adaptive controller is used here to learn the unknown dynamics and deals with the external uncertainties via a set of Fourier series to achieve velocity tracking. The proposed HFSMAC has been verified to lead to good robustness levels, effective learning, and accurate trajectory tracking. Computer simulations have been conducted to validate the theoretical developments confirming the efficacy and robustness of the proposed scheme. Finally, a comparative study with a PID controller is presented to further prove the superior performance of the proposed HFSMAC.

AB - The trajectory tracking of a differential-driven mobile robot (DDMR) with uncertainties and unknown dynamics is investigated using a hierarchical fuzzy sliding-mode adaptive controller (HFSMAC). First, the position error between the actual DDMR and the virtual reference DDMR with respect to the world frame is determined. Based on the aforementioned position error, fuzzy sliding-mode control is used to generate the virtual reference input and attain position tracking. It is well known that the performance and stability of a closed-loop system often deteriorate in the presence of uncertainties. Therefore, a function approximation technique (FAT)-based adaptive controller is used here to learn the unknown dynamics and deals with the external uncertainties via a set of Fourier series to achieve velocity tracking. The proposed HFSMAC has been verified to lead to good robustness levels, effective learning, and accurate trajectory tracking. Computer simulations have been conducted to validate the theoretical developments confirming the efficacy and robustness of the proposed scheme. Finally, a comparative study with a PID controller is presented to further prove the superior performance of the proposed HFSMAC.

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