Coot optimization algorithm-tuned neural network-enhanced PID controllers for robust trajectory tracking of three-link rigid robot manipulator

Robotic manipulators are nonlinear systems, multi-input multi-output, highly coupled and complicated whose performance is negatively impacted by external disturbances and parameter un-certainties. Therefore, the controllers designed for such systems must be capable of managing their complexity. The...

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Bibliographic Details
Published in:Heliyon Vol. 10; no. 13; p. e32661
Main Authors: Mohamed, Mohamed Jasim, Oleiwi, Bashra Kadhim, Azar, Ahmad Taher, Hameed, Ibrahim A.
Format: Journal Article
Language:English
Published: England Elsevier Ltd 15.07.2024
Elsevier
Subjects:
3-Link rigid robotic manipulator
algorithms
Coot optimization algorithm
model uncertainty
Neural network
Nonlinear system
PID controller
robots
Trajectory tracking
PID controller
Coot optimization algorithm
Trajectory tracking
Neural network
Nonlinear system
3-Link rigid robotic manipulator
ISSN:2405-8440, 2405-8440
Online Access:Get full text
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Summary:Robotic manipulators are nonlinear systems, multi-input multi-output, highly coupled and complicated whose performance is negatively impacted by external disturbances and parameter un-certainties. Therefore, the controllers designed for such systems must be capable of managing their complexity. The main aim of this study is to tackle the trajectory tracking issue of the three-Link Rigid Robot Manipulator (3-LRRM) based on designing three control structures using a combi-nation Neural Network (NN) with Proportional, Integral and Derivative (PID) actions named Neural Controller Like PIPD (NN-PIPD) controller, Neural Network plus PID (NN + PID) controller NN + PID controller and Elman Neural Network Like PID (ELNN-PID) controller. The parameters of the proposed controllers are adjusted utilizing the Coot Optimization Algorithm (COOA) in order to reduce the Integral Time Square Error (ITSE). A novel objective function for tuning process to produce a controller with minimum value of the chattering in the control signal is proposed. The performance of the proposed controllers is evaluated in terms of disturbance rejection, model uncertainty, fluctuating initial conditions and reference trajectory tracking. According to the simulation results proved that the suggested NN-PIPD controller outperforms all other proposed controller structures for tracking performance, stability, and robustness. As a result of the com-parison analysis the optimal controller was considered to be an NN-PIPD controller for tracking trajectory, rejecting disturbances, and parameter variation with minimizing ITSE of 0.001777.
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ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2024.e32661