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New Fusion Algorithm-Reinforced Pilot Control for an Agricultural Tricopter UAV

Author

Listed:
  • Huu Khoa Tran

    (Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

  • Juing-Shian Chiou

    (Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan 71005, Taiwan)

  • Viet-Hung Dang

    (Faculty of Information Technology, Duy Tan University, Danang 50000, Vietnam)

Abstract

Currently, fuzzy proportional integral derivative (PID) controller schemes, which include simplified fuzzy reasoning decision methodologies and PID parameters, are broadly and efficaciously practiced in various fields from industrial applications, military service, to rescue operations, civilian information and also horticultural observation and agricultural surveillance. A fusion particle swarm optimization (PSO)–evolutionary programming (EP) algorithm, which is an improved version of the stochastic optimization strategy PSO, was presented for designing and optimizing controller gains in this study. The mathematical calculations of this study include the reproduction of EP with PSO. By minimizing the integral of the absolute error (IAE) criterion that is used for estimating the system response as a fitness function, the obtained integrated design of the fusion PSO–EP algorithm generated and updated the new elite parameters for proposed controller schemes. This progression was used for the complicated non-linear systems of the attitude-control pilot models of a tricopter unmanned aerial vehicle (UAV) to demonstrate an improvement on the performance in terms of rapid response, precision, reliability, and stability.

Suggested Citation

  • Huu Khoa Tran & Juing-Shian Chiou & Viet-Hung Dang, 2020. "New Fusion Algorithm-Reinforced Pilot Control for an Agricultural Tricopter UAV," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:9:p:1499-:d:408801
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    References listed on IDEAS

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    1. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
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    1. Xuelin Zhang & Xiaobin Xu & Xiaojian Xu & Pingzhi Hou & Haibo Gao & Feng Ma, 2023. "Intelligent Adaptive PID Control for the Shaft Speed of a Marine Electric Propulsion System Based on the Evidential Reasoning Rule," Mathematics, MDPI, vol. 11(5), pages 1-23, February.

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