Particle Swarm Optimization and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking

Applied Sciences

Nada El Gmili¹  Hassan Ayad¹  Abdeljalil El Kari¹  Mostafa Mjahed² 

[1] Faculty of Science and Technology, Cadi Ayyad University, Marrakesh 40000, Morocco;Royal School of Aeronautics, Marrakesh 40000, Morocco;

关键词: control;    quadrotor;    nonlinear;    PSO;    particle swarm optimization;    cuckoo search;   

DOI  :  10.3390/app9081719

来源: DOAJ

【 摘 要 】

This paper explores the full control of a quadrotor Unmanned Aerial Vehicles (UAVs) by exploiting the nature-inspired algorithms of Particle Swarm Optimization (PSO), Cuckoo Search (CS), and the cooperative Particle Swarm Optimization-Cuckoo Search (PSO-CS). The proposed PSO-CS algorithm combines the ability of social thinking in PSO with the local search capability in CS, which helps to overcome the problem of low convergence speed of CS. First, the quadrotor dynamic modeling is defined using Newton-Euler formalism. Second, PID (Proportional, Integral, and Derivative) controllers are optimized by using the intelligent proposed approaches and the classical method of Reference Model (RM) for quadrotor full control. Finally, simulation results prove that PSO and PSO-CS are more efficient in tuning of optimal parameters for the quadrotor control. Indeed, the ability of PSO and PSO-CS to track the imposed trajectories is well seen from 3D path tracking simulations and even in presence of wind disturbances.

【 授权许可】

Unknown