Adaptive differentiator via continuous terminal sliding mode controller for UAV piloting

Abstract Piloting UAVs in challenging real flight conditions, particularly in the presence of external disturbances, poses a significant hurdle. These disturbances, if not adequately addressed in the controller design phase, can severely impact performance or even lead to instability. Consequently, the control of UAVs in adverse weather conditions has become a prominent area of research. Notably, various approaches, including the utilization of the High Order Sliding Mode technique (HOSM) for autopilot design, have been proposed. Despite its robustness and simplicity in application, High Order Sliding Mode Control (HOSMC) has been met with skepticism due to the chattering phenomenon induced by its discontinuous control effects. The inherent challenges associated with HOSMC encompass not only chattering but also singularities. To tackle these issues, a proposed solution involves integrating adaptive differentiators with the continuous terminal sliding mode controller technique for UAV piloting. This approach aims to strike a balance between error reduction and robustness to noise, offering enhanced accuracy within a specific frequency range, irrespective of algorithmic gain tuning. Moreover, this article introduces an innovative approach employing real-time virtual reality environments for UAV piloting, leveraging the readily available Commercial Off-the-Shelf (COTS) Game, Microsoft Flight Simulator (MSFS). This method serves dual purposes: enhancing UAV piloting techniques and serving as a pedagogical tool to reinforce learners’ understanding in the aeronautical domain. By simulating real-world flight scenarios in a controlled virtual environment, this approach not only enhances the practical skills of UAV operators but also provides a safe and cost-effective means of training and experimentation.