ct 22(31): e5

Research Article

Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)

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  • @ARTICLE{10.4108/eetct.v9i31.1922,
        author={Abdullah Al Gizi},
        title={Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)},
        journal={EAI Endorsed Transactions on Creative Technologies},
        volume={9},
        number={31},
        publisher={EAI},
        journal_a={CT},
        year={2022},
        month={8},
        keywords={Proportional-Integral-Derivative Controller (PIDC), Quadcopter Aerial Vehicle (QAV), Particle Swarm Optimization (PSO)},
        doi={10.4108/eetct.v9i31.1922}
    }
    
  • Abdullah Al Gizi
    Year: 2022
    Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)
    CT
    EAI
    DOI: 10.4108/eetct.v9i31.1922
Abdullah Al Gizi1,*
  • 1: Southern Technical University
*Contact email: abdullah.algizi@stu.edu.iq

Abstract

Inspection of the faults and damages in high voltage transmission lines is not only unsafe and costly but also a very time-consuming process. In addition, it demands highly skilled manpower for the operation at tens of meters above the ground on cables carrying thousands of Volts. Meanwhile, the Quadcopter Aerial Vehicle (QAV) system became a popular alternative for aerial photography applications due to its low cost, ease of usage, and fast response wherein the proportional-integral-derivative controller (PIDC) is used. The PID controller compares the expected location of the drone with the actual measured position thereby can accurately detect the faults in the transmission lines. Based on these factors, in this study, the flight simulation is done according to the desired flight path, and drone imagery is used for (insulator, power line, and porcelain) flaw identification. Furthermore, three movements (roll, pitch, and yaw) of the quadcopter were controlled by different PIDC that were optimized using the particle swarm optimization (PSO). The MATLAB/Simulink application was used to develop the system and simulate the results (R2021b). This clearly suggested that the quadcopter continues to fly on a trajectory with minimum inaccuracy, wherein the PIDC operated as a closed-loop adaptive controller. Finally, the PSO-PIDC outperformed the PIDC due to the critical nature of manual gain modification for quadcopter flight stability.