考虑输入饱和的固定翼无人机自适应增益滑模控制

针对复杂环境下的固定翼无人机飞行控制问题，考虑输入饱和以及复杂外界干扰的影响，提出一种基于自适应滑模控制方法的固定翼无人机飞行控制策略。首先，对固定翼无人机模型进行介绍，将模型分为姿态子系统和速度子系统；其次，针对姿态子系统和速度子系统的特点以及控制需求，分别采用自适应多变量螺旋滑模和自适应快速超螺旋滑模设计姿态控制器和速度控制器，该策略无需设计干扰观测器对外界干扰进行估计，仍然可以实现固定翼无人机对姿态参考指令和速度参考指令的有限时间精确跟踪，并基于Lyapunov的稳定性分析方法证明了闭环系统的稳定性。最后，对本文所提出的控制策略进行了仿真验证，结果表明该控制策略具有良好的控制性能。

Adaptive-gain sliding mode control for fixed-wing UAVs with input saturation

Under the effects of complex flight environments, a control strategy for fixed-wing UAVs based on the adaptive sliding mode algorithm is proposed considering external disturbances and the input saturation. Firstly, a fixed-wing UAV model is introduced and further divided into an attitude subsystem and a velocity subsystem. Then, according to different characteristics and control requirements of the two subsystems, a novel adaptive multivariable twisting algorithm and a novel adaptive-gain fast super twisting sliding mode algorithm are proposed to design an attitude controller and a velocity controller for a fixed-wing UAV respectively. In this control strategy, the observer is not needed to estimate the disturbance. The stability of the closed loop systems is proved based on Lyapunov stability analysis. Finally, simulations are conducted to demonstrate the effectiveness and favorable control performance of the proposed strategy.