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Model-Based Optimization Approach for PID Control of Pitch–Roll UAV Orientation

Author

Listed:
  • Orlando Arrieta

    (Instituto de Investigaciones en Ingeniería, Facultad de Ingeniería, Universidad de Costa Rica, San José 11501-2060, Costa Rica
    Departament de Telecomunicació i d’Enginyeria de Sistemes, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain)

  • Daniel Campos

    (Instituto de Investigaciones en Ingeniería, Facultad de Ingeniería, Universidad de Costa Rica, San José 11501-2060, Costa Rica)

  • Javier Rico-Azagra

    (Control Engineering Research Group, Electrical Engineering Department, University of La Rioja, 26004 Logroño, Spain)

  • Montserrat Gil-Martínez

    (Control Engineering Research Group, Electrical Engineering Department, University of La Rioja, 26004 Logroño, Spain)

  • José D. Rojas

    (Instituto de Investigaciones en Ingeniería, Facultad de Ingeniería, Universidad de Costa Rica, San José 11501-2060, Costa Rica
    Departament de Telecomunicació i d’Enginyeria de Sistemes, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain)

  • Ramon Vilanova

    (Departament de Telecomunicació i d’Enginyeria de Sistemes, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain)

Abstract

This study focuses on the modeling and control optimization of the pitch–roll angles orientation in a quad-rotor UAV (unmanned aerial vehicle) drone system. To address the control challenge, PID (proportional–integral–derivative) controllers are used, which have been tuned through a model-based optimization approach. A non-linear model of the system is obtained and further validated experimentally. The model is implemented in Simulink to conduct model-based optimization. The controller design uses an IMC (internal model control) model-based approach to establish the initial parameters for a PID controller. In the subsequent design phase, a multiobjective approach is taken, incorporating weighted cost functions that account for IAE (integral absolute error) and ITAE (integral of time-weighted absolute error) forms, along with battery usage. The outcomes of this design are showcased through simulations and real-world platform testing.

Suggested Citation

  • Orlando Arrieta & Daniel Campos & Javier Rico-Azagra & Montserrat Gil-Martínez & José D. Rojas & Ramon Vilanova, 2023. "Model-Based Optimization Approach for PID Control of Pitch–Roll UAV Orientation," Mathematics, MDPI, vol. 11(15), pages 1-17, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:15:p:3390-:d:1209628
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    References listed on IDEAS

    as
    1. Xiaodong Zhang & Xiaoli Li & Kang Wang & Yanjun Lu, 2014. "A Survey of Modelling and Identification of Quadrotor Robot," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-16, October.
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