Abstract:
Quadcopters have garnered significant interest within the UAV community due to their
wide-ranging applications in both military and civilian sectors. This study presents op timized controllers designed for precise regulation of quadcopter attitude and heading.
The control strategies employed include a Sliding Mode Controller (SMC) and a Ter minal Super Twisting SMC (TST-SMC), both aimed at addressing trajectory tracking
challenges. To enhance performance, the Red Fox Optimization (RFO) algorithm is
utilized, focusing on multi-objective functions such as the Integral of Squared Error
(ISE), Integral of Absolute Error (IAE), Integral of Time-weighted Absolute Error
(ITAE), and Mean Squared Error (MSE).
The numerical results indicate that TST-SMC outperforms SMC across several
performance metrics. For instance, in X-position control, TST-SMC achieves a lower
ISE of 26.7457 compared to SMC’s 7.5726. Similarly, for Y-position control, TST SMC reduces ITSE to 177.7704, whereas SMC achieves 1.8734. Moreover, in Z-position
control, TST-SMC demonstrates superior accuracy with an IAE of 1.7291 compared
to 9.6973 for SMC. These findings confirm that TST-SMC provides enhanced control
accuracy, particularly in terms of IAE and ITSE metrics.
The Integral of Time-weighted Absolute Error (ITAE) emerges as the most suitable
multi-objective function for optimizing TST-SMC, as it effectively improves transient
response and tracking accuracy. The nonlinear quadcopter model, developed in MAT LAB, incorporates aerodynamic effects and gyroscopic moments, ensuring a realistic
system representation. Furthermore, Lyapunov stability analysis verifies the stability
of the system, while graphical and tabular comparisons provide a comprehensive eval uation of the controllers. Overall, the results demonstrate that TST-SMC, optimized
through ITAE-focused RFO, delivers robust and accurate performance for precise at titude control in quadcopter systems.
