Comparison of Metaheuristic Optimization Algorithms for Quadrotor PID Controllers

被引:0
作者
Demir, Batikan Erdem [1 ]
Demir, Funda [1 ]
机构
[1] Karabuk Univ, Mechatron Engn Dept, Demir Celik Campus, TR-78050 Karabuk, Turkiye
来源
TEHNICKI VJESNIK-TECHNICAL GAZETTE | 2023年 / 30卷 / 04期
关键词
ABC; FA; GA; PID controller; PSO; quadrotor; CONTROL-SYSTEM; DESIGN; TRACKING; ATTITUDE;
D O I
10.17559/TV-20221108150435
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the present study, different solution methods are discussed in order to control the quadrotor with the most optimal PID parameters for the determined purposes. One of these methods is to make use of meta-heuristic algorithms in control systems. There are some limitations of using a PID controller as a classical construct. However, it is thought that more successful results will be obtained by optimizing its parameters through meta-heuristic algorithms. Initially, the mathematical model of the vehicle was created in MATLAB/Simulink. Then, genetic algorithms (GA), artificial bee colony (ABC), particle swarm optimization (PSO) and firefly algorithms (FA) were determined respectively as optimization methods. And these optimization methods used to determine the PID control parameters are applied to the developed mathematical model in the MATLAB/Simulink environment. In addition, the performances of the optimization methods are evaluated according to the comparison criteria. As a result of the comparison carried out according to ITAE (Integral Time Absolute Error) fitness criteria, ABC (1.2% -4.4%) in terms of altitude, FA (4% -13%) in terms of roll angle, GA (13% -%21) in terms of pitch angle, and PSO (4% -%15) in terms of yaw angle has been more successful than other methods.
引用
收藏
页码:1096 / 1103
页数:8
相关论文
共 25 条
[1]  
Ahmed AH, 2016, ICENCO 2016 - 2016 12TH INTERNATIONAL COMPUTER ENGINEERING CONFERENCE (ICENCO) - BOUNDLESS SMART SOCIETIES, P123, DOI 10.1109/ICENCO.2016.7856456
[2]   PID control system analysis, design, and technology [J].
Ang, KH ;
Chong, G ;
Li, Y .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2005, 13 (04) :559-576
[3]  
Bouabdallah S., 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), P2451
[4]   Full control of a quadrotor [J].
Bouabdallah, Samir ;
Siegwart, Roland .
2007 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-9, 2007, :153-158
[5]   Real-time trajectory tracking of an unmanned aerial vehicle using a self-tuning fuzzy proportional integral derivative controller [J].
Demir, Batikan E. ;
Bayir, Raif ;
Duran, Fecir .
INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES, 2016, 8 (04) :252-268
[6]   Attitude controller optimization of four-rotor unmanned air vehicle [J].
Erkol, Huseyin Oktay .
INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES, 2018, 10 (01) :42-49
[7]   Real-Time Human Detection and Tracking Using Quadcopter [J].
George, Rana Praful ;
Prakash, V. .
INTELLIGENT EMBEDDED SYSTEMS, ICNETS2, VOL II, 2018, 492 :301-312
[8]  
Goldber D. E., 1988, Machine Learning, V3, P95, DOI 10.1023/A:1022602019183
[9]   Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System [J].
Goud, Harsh ;
Sharma, Prakash Chandra ;
Nisar, Kashif ;
Haque, Muhammad Reazul ;
Ibrahim, Ag Asri Ag ;
Yadav, Narendra Singh ;
Swarnkar, Pankaj ;
Gupta, Manoj ;
Chand, Laxmi .
CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 72 (02) :3481-3492
[10]   Parameters tuning of a quadrotor PID controllers by using nature-inspired algorithms [J].
Hasseni, Seif-El-Islam ;
Abdou, Latifa ;
Glida, Hossam-Eddine .
EVOLUTIONARY INTELLIGENCE, 2021, 14 (01) :61-73