面向灾后废墟、工业管道等狭窄受限空间的协同搜索任务，具备窄机身、长续航特性的小型纵列双旋翼无人机(Small Tandem-Rotor UAV, STR-UAV)编队是一类理想的作业平台。针对此类复杂作业环境下输入饱和、外部扰动与执行器故障并存的多重约束挑战，本文提出了一种自适应分布式预设时间编队容错控制策略。首先，设计了一个新颖的光滑饱和函数，解决了同号非对称的输入饱和约束问题；其次，构建了一个新颖的预设时间滑模面，实现了编队误差在用户预设时间内的收敛；然后，融合前述光滑饱和函数、预设时间滑模面和自适应方法，提出了一个自适应分布式预设时间编队容错控制策略；最后，基于Lyapunov理论严格证明了所提编队控制策略的预设时间稳定性，并进行了数值仿真。仿真结果不仅证实了所提控制策略的有效性，更通过定性分析与定量对比凸显了其相对于现有部分方法的优越性。

For collaborative search missions in confined spaces such as disaster-stricken ruins and industrial pipelines, the formation of small tandem-rotor unmanned aerial vehicles (STR-UAVs) with narrow fuselages and long endurance forms an ideal operational platform. To address the multiple constraints of input saturation, external disturbances, and actuator failures in such complex operational environments, an adaptive distributed prescribed-time fault-tolerant formation control strategy is proposed. Firstly, a novel smooth saturation function is designed to address the issue of input saturation constraints with asymmetric sign. Secondly, a novel prescribed-time sliding mode surface is constructed, achieving the convergence of formation errors within a user-defined time. Thirdly, an adaptive distributed prescribed-time fault-tolerant formation control strategy is proposed by integrating the aforementioned smooth saturation function, prescribed-time sliding mode surface, and adaptive method. Finally, based on Lyapunov theory, the prescribed-time stability of the proposed formation control strategy is rigorously proven, and numerical simulations are conducted. The simulation results not only validate the effectiveness of the proposed control strategy but also highlight its superiority over some existing methods through qualitative analysis and quantitative comparisons.