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This is a Experimental Study study.

September 12, 2025An International Journal of Optimization and Control Theories & Applications (IJOCTA)Open Access

African vultures optimization-based hybrid neural network–proportional-integral-derivative controller for improved robot manipulator tracking

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Authors

BOBashra Kadhim OleiwiUniversity of Technology - Iraq MMMohamed Jasim MohamedUniversity of Technology - Iraq AAAhmad Taher AzarPrince Sultan University

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Implication

This analysis finds that a neural network-PID controller significantly improves stability and accuracy in robotic manipulators, suggesting a new approach for trajectory tracking.

Key Points

The NN-PID controller shows superior tracking accuracy and stability over conventional methods.
Integral time square error values for NN-PID controller reached an impressive 0.073968 under challenging conditions.
Robustness testing revealed NN-PID's effectiveness against external disruptions and parameter variations.
The African vultures optimization algorithm played a crucial role in fine-tuning the controller parameters.

Cite This Study

Oleiwi et al. (2025) studied this question.

synapsesocial.com/papers/68d44b3f31b076d99fa55101 https://doi.org/10.36922/ijocta025080032

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Implication

This analysis finds that a neural network-PID controller significantly improves stability and accuracy in robotic manipulators, suggesting a new approach for trajectory tracking.

African vultures optimization-based hybrid neural network–proportional-integral-derivative controller for improved robot manipulator tracking

Discussion

Member takes

Implication

Key Points

Cite This Study

African vultures optimization-based hybrid neural network–proportional-integral-derivative controller for improved robot manipulator tracking

Discussion

Member takes

Implication

Key Points

Cite This Study

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