Data‐Driven Adaptive Longitudinal Control With a Fuzzy‐Logic‐Based Dynamic Internal Model for Carrier‐Based UAV Landing

Abstract

This article addresses the landing control problem of carrier‐based unmanned aerial vehicles (UAVs) subject to strong nonlinearities, measurement fading, and external disturbances. First, an enhanced data‐driven adaptive control scheme is proposed which integrates an adaptive fuzzy approximator and a dynamic internal compensator. Then, the proposed method adopts the measurement information to solve the nonlinear uncertainties and reduce information loss by measurement fading while suppressing complex disturbances induced by airwake and deck motion. This design enables the controller to operate without requiring an accurate system model. Furthermore, a systematic and rigorous theoretical analysis is conducted to verify the convergence of the designed controller. Numerical simulations further show that the controller maintains strong robustness, fast response to dynamic environments, and high landing accuracy under different sea states and complex disturbance levels. These results confirm the effectiveness of the proposed approach and highlight its considerable potential for practical application in carrier‐based UAV landing systems.