Predetermined-time super-twisting prescribed performance control for morphing aircraft under external disturbances

High-speed morphing aircraft is significantly more complex than conventional aircraft due to its unique structure, dynamic, and environmental characteristic, characterized by strong coupling and nonlinear dynamics. Traditional controllers are unable to achieve high control quality under severe external disturbances and parameter perturbations, nor can they meet the requirements for fast response, strong robustness, and high-precision control under multiple operational constraints. To address these challenges, this paper firstly establishes a comprehensive kinematic and dynamic model of the morphing aircraft. The dynamic model is conducted using the Newton-Euler vector mechanics approach, which considers the translational and rotational motions of both the fuselage and wings. The derived multi-rigid body dynamical equations analyze aerodynamic forces, gravitational forces, thrust, and control torques, while effectively solving the coupling effects between the fuselage and wing motions. Subsequently, a novel predetermined-time prescribed performance controller is proposed in this paper, which effectively limits the transient and steady-state performance of the morphing aircraft. The proposed controller transforms constrained tracking errors into unconstrained ones, ensuring that the original tracking error satisfies prescribed bounds. Building on this framework, a super-twisting algorithm and double power reaching law are introduced to accelerate convergence and suppress system chattering. Finally, simulation results demonstrate that the controller achieves stable control of high-speed morphing aircraft during the morphing process, effectively satisfying flight constraints in complex and dynamic environments. In addition, practical implementation issues of the proposed controller have been considered, such as sensor noise, actuator delays, and computational feasibility, supporting its feasibility in real-time flight scenarios.