Docking Controller for Autonomous Aerial Refueling With Adaptive Dynamic Surface Control

Abstract

The docking controller for autonomous aerial refueling (AAR) is intractable considering the high precision requirement and the complex disturbances of multiple environment flows. To solve the problems in the docking phase of AAR, such as the uncertainties of the aerodynamic parameters of receiver aircraft and the disturbances acting on the receiver aircraft, an adaptive dynamic surface control (ADSC) scheme based on radical basis function neural network (RBF-NN) is presented in this paper. Firstly, a nonlinear model of longitudinal dynamics of the receiver aircraft relative to the tanker aircraft is established, which incorporates the tanker vortex term. Secondly, a nonlinear strict-feedback form is introduced to design an adaptive dynamic surface controller with RBF-NN. Thirdly, the upper bounds of the ''total disturbances'' are estimated with the adaptive law, and the uncertain aerodynamic parameters of receiver aircraft are estimated with RBF-NN. It is proved that the proposed controller can guarantee the uniform boundedness of all the signals in the closed-loop system using Lyapunov theory. Finally, simulation results demonstrate the effectiveness of the proposed controller for the docking control of AAR. INDEX TERMS Autonomous aerial refueling, docking controller, adaptive dynamic surface control, RBF neural network.

Management and intelligent control of in‐flight fuel distribution in a commercial aircraft

“…Fuel management is an important issue in aviation for safety and efficiency reasons. It comprises initial on‐ground refuelling (Plaza & Santos, 2020), aerial refuelling (mainly in the air force), (Lee et al, 2020; Li et al, 2020; Wu et al, 2020), and the flow of combustible amongst aircraft fuel tanks during the flight.…”