The quadrotor dynamic modeling and study of meta-heuristic algorithms performance on optimization of PID controller index to control angles and tracking the route

Ata Jahangir Moshayedi, Mahyar Gheibollahi, Liefa Liao

Abstract


In the last decade, because of the unique specification of vertical fliers, scientists and researchers had a special focus on them. The particular abilities of these fliers can be mentioned such as: high maneuver ability, low expenses, decrease in radar identifier and low threat for the human life. They also have no limitation in dimension. Moreover, because of some applications like photography, topography, news coverage, study of power lines and aerology analysis, they can be notable for using. These fliers also are significantly important because of monitoring in urban regions, agricultural harvest and spray poison, illegal imports, exports administration and fire distinction in order to control the fire. Besides, seek and rescue missing people and also natural disasters can be pre-determined which causes stimulus investigators to act and put different topics in front of them. One of these fields is using meta-heuristic algorithms with the capability of using in control systems. The PID controller as a classic model has some limitations, but by optimization of special index through meta-heuristic algorithms, it has shown acceptable results. In this study, first, the history of vertical fliers and quadrotor are investigated. Then, after a review of overused methods, the quadrotor control has been done. Afterward, the cinematic and dynamic of quadrotor is presented. Next by designing of PID controller, PID index optimization by nature inspired algorithm, particle swarm optimization (PSO), genetic algorithms (GA), and firefly algorithms (FA) have been studied. Dynamic system, controller and mentioned optimization methods of PID controller index have also been implemented in MATLAB software. Also, with due attention to the comparison criteria the PID-PSO controller has shown the best performance. Next, by applying challenging routes, the stability of controller in the simulation is evaluated. Then, making quadrotor is done in practice along with introducing the used implementation of PID-PSO controller results on the real robot, and its stability is evaluated practically.


Keywords


Firefly algorithm; Genetic algorithm; Optimization algorithms; Particle swarm optimization algorithm; PID controller; Quadrotor; Robot; UAV; Unmanned flier

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DOI: http://doi.org/10.11591/ijra.v9i4.pp%25p
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Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.