Optimal Nonlinear backstepping controller design of a Quadrotor-Slung load system using particle Swarm Optimization

被引:20
作者
Baraean, Abdullah [1 ]
Hamanah, Waleed M. [2 ]
Bawazir, Ahmed [3 ]
Baraean, Saleh [4 ]
Abido, Mohammad A. [1 ,2 ,5 ]
机构
[1] King Fahd Univ Petr & Minerals, Coll Engn & Phys, Dept Elect Engn, Dhahran, Saudi Arabia
[2] King Fahd Univ Petr & Minerals, Res Inst, Interdisciplinary Res Ctr Renewable Energy & Power, IRC REPS, Dhahran, Saudi Arabia
[3] King Fahd Univ Petr & Minerals, Dept Comp Engn, Dhahran 31261, Saudi Arabia
[4] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
[5] King Fahd Univ Petr & Minerals, KACARE Energy Res & Innovat Ctr, Dhahran, Saudi Arabia
关键词
Unmanned aerial vehicles (UAVs); Nonlinear Backstepping Con-troller (NBC); Particle Swarm Optimization algorithm (PSO); Lyapunov Theory; MODEL;
D O I
10.1016/j.aej.2023.01.050
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A backstepping control strategy for an underactuated quadrotor slung load system is presented in this paper. The issue of trajectory tracking for a cable-suspended load is addressed. A rigid body and a point mass are used to model the Quadrotor and slung-load, respectively. Lya-punov theory and backstepping technique are used to design the controller. Thrust and angular velocity control laws are carefully designed to ensure that the closed-loop system is asymptotically stable. The problem of finding the optimal set of parameters for the backstepping controller gains is formulated as an optimization problem and solved with the Nonlinear Backstepping Controller using Particle Swarm Optimization algorithm (NBC-PSO). The effectiveness of the optimized con-troller is established by simulation results done utilizing MATLAB/Simulink and compared with a conventional Nonlinear Backstepping Controller (NBC). It was observed that, the proposed NBC-PSO achieves approximately 14% improvement in load position trajectory convergence to the desired trajectory. The results confirm that the NBC-PSO controller is effective, and the controller converges faster than other controllers. (c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:551 / 560
页数:10
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