PARTICLE SWARM OPTIMIZATION BASED OPTIMAL PID CONTROLLER FOR QUADCOPTERS

被引：5

作者：

Sonugur, Guray ^{[1
]}

Gokce, Celal Onur ^{[2
]}

Koca, Yavuz Bahadir ^{[3
]}

Inci, Seyket Semih ^{[1
]}

Keles, Zeynep ^{[1
]}

机构：

[1] Afyon Kocatepe Univ, Fac Technol, Dept Mechatron Engn, TR-03200 Afyon, Turkey

[2] Afyon Kocatepe Univ, Fac Engn, Dept Elect Engn, TR-03200 Afyon, Turkey

[3] Afyon Kocatepe Univ, Afyon Vocat Sch, Dept Automat & Control, TR-03200 Afyon, Turkey

来源：

COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES | 2021年 / 74卷 / 12期

关键词：

UAV; PSO; quadcopter; robot control; NEURAL-NETWORK; ATTITUDE; DESIGN; MODEL;

D O I：

10.7546/CRABS.2021.12.11

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 novel particle swarm optimization (PSO) based optimal PID controller for quad-copters is proposed in this paper. A mathematical model of the quadcopter is derived first. A PID controller for attitude control is proposed. Parameters of the PID controller are found using PSO algorithm. Two stages of optimization are conducted. The novelty of this study is that the two stages are conducted differently; in the first stage no disturbance is used while in the second stage several different disturbance magnitudes are used to fine tune the controller. In the first stage, coarse parameters are found with zero disturbance experiments. These parameters are fed as initial parameters for a second stage of optimization. In the second stage, parameters are fine-tuned under various magnitudes of disturbance. Disturbance is used to simulate wind, noise and other unpredictable effects. Results are given as figures and summarized as a table. Simulation results show that the second stage of optimization clearly enhances performance of disturbance rejection.

引用

页码：1806 / 1814

页数：9

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