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IMPLEMENTATION OF FUZZY ADAPTIVE NEURONAL CONTROL APPLIED TO TRAJECTORY TRACKING OF AN AUTONOMOUS UNMANNED SURFACE VEHICLE

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JANUARY-DECEMBER 2024   -  Volume: 11 -  Pages: [ 16 pp.]

DOI:

https://doi.org/10.52152/DNT11251

Authors:

ABIGAIL MARÍA ELENA RAMÍREZ MENDOZA
-
FILIBERTO MUÑOZ PALACIOS
-
WEN YU

Disciplines:

  • Instrumentation technology (INGENIERIA DE CONTROL )

Downloads:   15

How to cite this paper:  
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Received Date :   23 April 2024

Reviewing Date :   20 February 2024

Accepted Date :   10 June 2024


Key words:
Unmanned autonomous surface vehicle, fuzzy adaptive neurons, trajectory tracking, PID implementation, Arduino Mega, Vehículo de superficie no tripulado autónomo, control neuronal adaptativo difuso, neuronas adaptativas difusas, seguimiento de trayectoria, implementación de un controlador Proporcional Integral Derivativo, Arduino Mega
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

ABSTRACT:
This article presents the hardware implementation of the fuzzy adaptive neural control law for trajectory tracking based on a simplified model of the navigation system of an autonomous unmanned surface vehicle prototype for water quality monitoring. The parameters of the simplified model are estimated. Trajectory tracking is carried out in-line by fuzzy adaptive neurons for tuning the gains of a Proportional Integral Derivative controller (PID). The stability analysis is developed. Simulations were obtained at Matlab®/Simulink for circular trajectories and the implementation in Arduino Mega boards, very good precision is obtained for the experimental results in a diving pit.

Keywords: Autonomous unmanned surface vehicle, fuzzy adaptive neuronal control, trajectory tracking, implementation of a Proportional Integral Derivative controller, Arduino Mega.

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