What type of study is this?

This is a Quantitative Study study.

October 5, 2025

Hybrid Particle Swarm Optimization Bacterial Foraging control an agricultural Quadcopter

Key Points

Enhanced controller performance was achieved using a hybrid algorithm integrating bacterial foraging and particle swarm optimization.
The hybrid algorithm outperformed traditional methods, indicating superior stability and reliability in quadcopter control parameters.
Numerical simulations validated the effectiveness of the proposed controller, confirming fast responses and accurate performance.
The developed controller aids in various agricultural applications, highlighting its potential impact on farming efficiency.

Abstract

This article proposes a hybrid algorithm that combines Bacterial Foraging (BF) and Particle Swarm Optimization (PSO) to optimize the control parameters: Integral (I) controller plus Fuzzy-like Proportional and Derivative (Fuzzy-like PD) as the Fuzzy Scaling Factors (FSF) of the Fuzzy controller. The fitness function integral of time multiplied absolute error (ITAE) was utilized as a minima criterion to assess the control design effectiveness. The proposed controller is then applied to pilot a UAV Quadcopter model for usage in a variety of agricultural applications, including field observation, crop health monitoring, pesticide spraying, disease detection, etc. The numerical simulations perform the validity of the fast responses, stable and reliable without error.

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Cite This Study

Tran et al. (Fri,) studied this question.

synapsesocial.com/papers/68e24e65d6d66a53c24738ee https://doi.org/https://doi.org/10.1177/13272314251379735

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