Observer-like State Augmented Model Reference Adaptive Robust Control of Fixed-wing UAV with Disturbances and Uncertainties

In this article, an observer-like state augmented model reference adaptive robust controller (OAMRARC) is proposed for fixed-wing UAV system with disturbances and uncertainties and inaccurate dynamic model. An output feedback controller is proposed to achieve the desired instruction tracking. The method in this article uses the original reference model to generate the tracking trajectory, uses the closed-loop reference model to construct the observer-like. Moreover, it adds robust items to improve the ability of system to resist disturbances. At the same time, the steady-state performance of the system is also improved, by reason of the state augmentation of the system based on the error integral. Lyapunov-based stability proofs show that the state errors converge exponentially. Finally, the effectiveness of the method is verified by simulating and analyzing the partial longitudinal model of the fixed-wing UAV. In the simulation, compared with the CRM method, the OAMRARC method in this article can effectively suppress the disturbance and improve the steady-state performance of the system.