ArticleHeliyon2024
Fuzzy logic controller for UAV with gains optimized via genetic algorithm.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Self-Tuning Minimal-Rule Fuzzy Logic Controller for High-Performance Induction Motor Drives.Sensors (Basel, Switzerland) · 2026Article
- Hybrid control structure employing fuzzy-sliding mode systems for the guidance of coaxial octorotor UAV.Scientific reports · 2026Article
- Fault-tolerant control of quadrotor unmanned aerial vehicle by using adaptive fuzzy T-S and linear matrix inversion approach.Scientific reports · 2026Article
- Optimal fuzzy-PID controller design for object tracking.Scientific reports · 2025Article
- Design and development of different adaptive MPPT controllers for renewable energy systems: a comprehensive analysis.Scientific reports · 2024Article
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Authors and funding
4 authors.
Funding
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Abstract
A gains optimizer of a fuzzy controller system for an Unmanned Aerial Vehicle (UAV) based on a metaheuristic algorithm is developed in the present investigation. The contribution of the work is the adjustment by the Genetic Algorithm (GA) to tune the gains at the input of a fuzzy controller. First, a typical fuzzy controller was modeled, designed, and implemented in a mathematical model obtained by Newton-Euler methodology. Subsequently, the control gains were optimized using a metaheuristic algorithm. The control objective is that the UAV consumes the least amount of energy. With this basis, the Genetic Algorithm finds the necessary gains to meet the design parameters. The tests were performed using the Matlab-Simulink environment. The results indicate an improvement, reducing the error in tracking trajectories from 30% in some tasks and following trajectories that could not be completed without a tuned controller in other tasks.
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