Fuzzy logic controller for UAV with gains optimized via genetic algorithm

被引：12

作者：

Rodriguez-Abreo, Omar ^{[1
]}

Rodriguez-Resendiz, Juvenal ^{[2
]}

Garcia-Cerezo, A. ^{[1
]}

Garcia-Martinez, Jose R. ^{[3
]}

机构：

[1] Univ Malaga, Space Robot Lab, Dept Syst Engn & Automat, C Ortiz Ramos S-N, Malaga 29071, Spain

[2] Univ Autonoma Queretaro, Fac Ingn, Queretaro 76010, Mexico

[3] Univ Veracruzana, Fac Ingn Elect & Comunicac, Poza Rica 93390, Ver, Mexico

来源：

HELIYON | 2024年 / 10卷 / 04期

关键词：

Fuzzy logic; UAV; Metaheuristic algorithm; Genetic algorithm; Optimization; TRACKING;

D O I：

10.1016/j.heliyon.2024.e26363

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：14

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