Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization

Abstract

This study focuses on designing a controller for trajectory tracking of quadcopters using advanced sliding-mode techniques. Specifically, an integral terminal sliding-mode control based on an adaptive barrier function with a super-twisting reaching law is employed to achieve precise trajectory tracking. The performance of the controller is enhanced by applying Particle Swarm Optimization to fine-tune the gain values. The nonlinear dynamics of the quadcopter are modeled using the Euler–Lagrange approach, followed by a Lyapunov stability analysis to verify the stability of the controller. The adaptive barrier function is used to prevent control signal saturation, while the third-order sliding-mode controller effectively reduces the chattering. Additionally, a saturation function is introduced to further mitigate the chattering effect. The effectiveness of the proposed approach is demonstrated through numerical simulations, and its performance is further validated through controller-in-the-loop implementation. The results show that the proposed method significantly improves trajectory-tracking accuracy.