Abstract
Morphing aircrafts can adapt to complex mission environments, making them a future trend in aircraft development. However, the complex environment poses significant challenges for aircraft flight control. This paper aims to investigate the attitude stability and accurate control method of morphing aircraft based on nominal model for the problems of multi-source disturbances and high model complexity. The proposed control strategy (APP-BSRBFNDO) integrates an improved Adaptive Prescribed Performance (APP) method, a Nonlinear Disturbance Observer based on the Radial Basis Function Neural Network (RBFNDO), and the Backstepping (BS) for autonomous attitude control of variable-span aircraft. Initially, the research uses an intermediate state of aircraft morphing as the standard model, treating the morphing of the aircraft and uncertainties introduced by the external environment as disturbances. This research establishes a dynamic model aimed at the control objective. The study introduces corresponding improvements in response to the limitations inherent in traditional Prescribed Performance Control (PPC) and Extended State Observer (ESO). It presents an autonomous disturbance rejection control method based on prescribed performance. Numerical simulations affirm the APPBSRBFNDO control method's robustness in aircraft morphing scenarios and disturbances. This approach significantly improves response overshoot and steady-state error compared to the conventional BSESO method.