Integrating Second Order Sliding Mode Control and Anomaly Detection Using Auto-Encoder for Enhanced Safety and Reliability of Quadrotor UAVs

This paper presents a comprehensive framework for enhancing the safety and reliability of quadrotor UAVs by integrating second-order sliding mode control (2-SMC) an advanced anomaly detection prediction system based on machine learning AI. The addresses challenges designing controllers quadrotors proposing novel manifold approach divided into two subsystems accurate position attitude tracking. also provides detailed analysis nonlinear coefficients using Hurwitz stability analysis. It demonstrates effectiveness proposed method through extensive simulation results. To further assess quadrotor, is integrated with tracking control. utilizes AI techniques to identify predict abnormal behaviours or faults in real time, enabling quickly effectively respond critical situations. promising robust safe UAVs. potential autonomous systems.