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Tuning of cascade PID controller gains of quadcopter under bounded disturbances using metaheuristic based research algorithm

Published online by Cambridge University Press:  11 April 2025

E.H. Çopur Open the ORCID record for E.H. Çopur [Opens in a new window] ,
E. Balta Open the ORCID record for E. Balta [Opens in a new window]  and
H.H. Bilgic Open the ORCID record for H.H. Bilgic [Opens in a new window]
E.H. Çopur*
Affiliation:
Department of Aerospace Engineering, Necmettin Erbakan University, Konya 42040, Türkiye
E. Balta
Affiliation:
Department of Aeronautical Engineering, Necmettin Erbakan University, Konya 42040, Türkiye
H.H. Bilgic
Affiliation:
Department of Aeronautical Engineering, Necmettin Erbakan University, Konya 42040, Türkiye
*
Corresponding author: E.H. Çopur; Email: ehcopur@erbakan.edu.tr
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Abstract

The proportional–integral–derivative (PID) controller remains widely used in industrial applications today due to its simplicity and ease of implementation. However, tuning the controller’s gains is crucial for achieving desired performance. This study compares the performance of PID controllers within a cascade control architecture designed for both position and attitude control of a quadcopter. Particle swarm optimisation (PSO), grey wolf optimisation (GWO), artificial bee colony (ABC), and differential evaluation (DE) methods are employed to optimally tune the PID parameters. A set of PID gains is determined offline by minimising various modified multi-objective functions based on different fitness measures: IAE, ISE, ITAE and ITSE. These measures are adapted as fitness functions for position and attitude control. A simulation study is conducted to determine which fitness function yields the optimal PID gains, as evidenced by the lowest values of the objective functions. In these simulations, two different desired trajectories are designed, and the controllers are applied to ensure the quadcopter tracks these trajectories accurately. Additionally, to test the robustness of the flight control architecture and the finely tuned PID controllers against various environmental effects and parametric uncertainties, several case scenarios are also explored.

Keywords

Cascade PID controllersearch algorithmmetaheuristic algorithmquadcopteroptimization
Type
Research Article
Information
The Aeronautical Journal , First View , pp. 1 - 23
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Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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