Nonlinear switching control surface bias for unmanned air vehicles (UAVs)

In this work, A nonlinear control surface bias observer system is designed for Unmanned Air Vehicles (UAVs). In working environments UAVs are highly unstable and depend on the bias in aileron and elevator control surfaces. Without controlling these parameters, UAVs cannot achieve high performance. Here, a nonlinear control bias observer system is developed and subsequently applied to unmanned aircraft which can be modeled with six degrees-of-freedom. The observer uses switching control to provide robustness to sensor noise and modeling errors. Lyapunov theory is applied to find the region of practical stability. Extended Kalman Filter results are compared with the nonlinear control bias observer and were simulated in Matlab. The results were obtained with and without sensor and model errors. The final results indicated that the variable structure bias observer was more robust to sensor and model noise compared to an Extended Kalman filter.