Altitude and Attitude Control of a Quadcopter Based on Neuro-Fuzzy Controller

Korkmaz, Deniz; Açıkgöz, Hakan; Üstündağ, Mehmet

doi:10.1007/978-981-16-8129-5_154

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2024

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“…Fuzzy methodology [22][23], and Iterative Learning Control (ILC) [24][25]. These intelligent control methods are adept at managing unpredictable, non-linear, timevarying, and non-deterministic systems [26].…”

Section: Kinematic Modelmentioning

confidence: 99%

A Particle Swarm Optimization Based Fuzzy Flcpi-Pso Controller for Quadcopter System

Baba,

Bounaama,

Bennaceur

et al. 2024

Communications

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The quadcopter persist as important roles across diverse applications, and the enhancement of their control efficacy has been the subject of extensive research. In this work, the authors proposed optimal Proportional Integral (PI) controller based Fuzzy Logic Control (FLC) for the roll, pitch, altitude, and yaw motions of the quadcopter system. The proposed technique uses the Particle Swarm Optimization (PSO) algorithm to tune the parameters of the FLC and enhance the quadcopter performance. The simulation results show that the proposed technique achieves smoothness of control and significant improvement over classical techniques, as the rise time and the settling time are reduced by 61 % and 66 %, respectively. These times are important for stabilizing the system's response speed and avoiding overshooting or oscillating. This indicates that the FLCPI-PSO can achieve the desired roll and altitude angles more rapidly and effectively.

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