This paper presents advanced simulation tools for a quadrotor Unmanned Aerial Vehicle (UAV) system equipped with four six-phase Permanent Magnet Synchronous Motors (PMSMs). A Cuckoo Optimization Algorithm (COA) is designed for tuning the parameters of the decentralized PI/PID controllers of quadrotor height, quadrotor attitude angles, motor’s rotational speeds, and motors’ currents. Current control and speed control are implemented by means of the Field Oriented Control (FOC) logic. COA optimizes Square Error (SE) cost functions of the error dynamics with respect to the quadrotor’s stabilization task. The PID tuning process consists of three cascaded phases: optimization of quadrotor motion dynamics, optimization of motor speed dynamics, and optimization of motor currents dynamics. This process is repeated for different hovering and maneuvering scenarios. Sensor noise and anti-wind-up functions are also implemented. Simulations results obtained by means of MATLAB/Simulink® demonstrate the effectiveness of the approach regarding simulation and control tuning for the coupled motor-quadrotor system.
Motor-Quadrotor Simulations based on FOC and Cuckoo PID Tuning / Rinaldi, Marco; Moslehi, Morteza. - ELETTRONICO. - (2025), pp. 1-7. (Intervento presentato al convegno 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) tenutosi a Antalya, Turkey nel 7-9 August 2025) [10.1109/ACDSA65407.2025.11166583].
Motor-Quadrotor Simulations based on FOC and Cuckoo PID Tuning
Rinaldi, Marco;
2025
Abstract
This paper presents advanced simulation tools for a quadrotor Unmanned Aerial Vehicle (UAV) system equipped with four six-phase Permanent Magnet Synchronous Motors (PMSMs). A Cuckoo Optimization Algorithm (COA) is designed for tuning the parameters of the decentralized PI/PID controllers of quadrotor height, quadrotor attitude angles, motor’s rotational speeds, and motors’ currents. Current control and speed control are implemented by means of the Field Oriented Control (FOC) logic. COA optimizes Square Error (SE) cost functions of the error dynamics with respect to the quadrotor’s stabilization task. The PID tuning process consists of three cascaded phases: optimization of quadrotor motion dynamics, optimization of motor speed dynamics, and optimization of motor currents dynamics. This process is repeated for different hovering and maneuvering scenarios. Sensor noise and anti-wind-up functions are also implemented. Simulations results obtained by means of MATLAB/Simulink® demonstrate the effectiveness of the approach regarding simulation and control tuning for the coupled motor-quadrotor system.Pubblicazioni consigliate
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https://hdl.handle.net/11583/3002852
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