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

Abstract

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. Lyapunov 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 controller 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.

Keywords

• Unmanned aerial vehicles (UAVs)
• Nonlinear Backstepping Controller (NBC)
• Particle Swarm Optimization algorithm (PSO)
• Lyapunov Theory