固定翼无人机紧密编队飞行时，僚机会受到长机尾流涡的干扰，增加了僚机控制器的设计难度，针对这一问题，本文首先提出了一种紧密编队气动耦合的建模方案，建立了大后掠翼无人机的尾流涡数学模型，研究了紧密编队气动耦合机理。接着，本文将预设时间控制的概念引入增量非线性动态逆控制，使控制器在具有强鲁棒性的同时兼顾快速收敛特性，基于此控制方法设计了僚机的内环控制器，使僚机气动参数受在到干扰的情况下能够准确的跟踪指令信号。由于增量非线性动态逆控制器在控制僚机内环时需要用到角速率和角加速度信号，但是在实际中通过传感器获得的角速率信号具有量测噪声，使用传统差分法会放大噪声，无法获得准确的角加速度信号，针对这一问题，本文将预定义时间控制的概念引入跟踪微分器，设计了一种改进跟踪微分器，在有噪声干扰情况下同时实现信号跟踪与微分的提取，兼具鲁棒性与快速性。用Lyapunov定理对提出的控制器进行了稳定性证明，并且对整个闭环系统进行了数字仿真，从仿真结果来看，本文设计的控制器达到预期效果，满足固定翼无人机紧密编队飞行时僚机的姿态控制需求。

During close formation flight of fixed-wing UAVs, the wingman aircraft is subjected to interference from the wake vortex of the leader aircraft, increasing the difficulty of designing the wingman’s controller. To address this issue, this paper first proposes a modeling method for aerodynamic coupling in close formation, establishes a mathemat-ical model of the wake vortex for highly swept-back wing UAVs, and studies the mechanism of aerodynamic cou-pling in close formation. Subsequently, the concept of prescribed-time control is introduced into incremental non-linear dynamic inversion (INDI) control, enabling the controller to achieve rapid convergence while maintaining strong robustness. Based on this control method, the inner-loop controller for the wingman aircraft is designed to ensure accurate tracking of command signals under aerodynamic disturbances.Since the incremental nonlinear dynamic inversion controller requires angular rate and angular acceleration signals for controlling the inner loop, but the angular rate signals obtained from sensors in practice contain measurement noise, traditional differentia-tion methods amplify noise and fail to provide accurate angular acceleration signals. To resolve this, the concept of predefined-time control is incorporated into the tracking differentiator, designing an improved tracking differentiator that achieves simultaneous signal tracking and differentiation extraction in noisy environments, combining robust-ness and rapidity.The stability of the proposed controller is proven using the Lyapunov theorem, and digital simula-tions of the entire closed-loop system are conducted. Simulation results demonstrate that the designed controller achieves the expected control effect and meets the attitude control requirements of the wingman aircraft during fixed-wing UAV close formation flight. Comparison with control methods from other literature shows that in close formation scenarios, the controller designed in this paper exhibits faster convergence, smaller steady-state error, and stronger robustness.