基于分层滑模面的固定翼无人机姿态跟踪控制

Attitude tracking control of fixed-wing UAV based on hierarchical sliding mode surface

针对固定翼无人机(unmanned aerial vehicle,UAV)控制系统控制难度大的问题,考虑外部扰动、模型偏差、状态误差、控制器微弱故障等复杂情况,设计分层滑模控制器。首先,考虑无人机受到多项干扰项的影响,给出该类情况下的姿态运动动力学模型;其次,提出一种分层滑模面,利用Barbalat稳定性理论证明滑模面的稳定性;然后,基于此分层滑模面设计控制器,通过控制无人机左右副翼控制器、左右升降翼控制器、方向翼控制器的输入信号,完成姿态轨迹跟踪过程;最后,通过仿真实验验证控制器的有效性与鲁棒性。结果表明,与基于神经网络的控制器相比,所提方法的控制输入更平稳,飞行轨迹更接近期望轨迹,稳态误差更趋近于0,控制参数更少。

A hierarchical sliding mode controller is designed to fix the complex control problem of the fixed-wing unmanned aerial vehicle(UAV)control system,which considers complex conditions such as external disturbance,model bias,state error and weak fault of the controller.Firstly,considering that UAV was affected by a number of interference terms,the attitude motion dynamics model was given.Secondly,a hierarchical sliding surface was proposed and its stability was proved by Barbalat stability theory.Then,based on the hierarchical sliding mode surface,the sliding mode controller was designed,and the attitude tracking process was completed by controlling the input signals of left and right aileron controllers,left and right lift controllers,and directional wing controllers.Finally,the effectiveness and robustness of the controller are verified by simulation experiments.Compared with the controller based on neural network,the control input is more stable,the flight trajectory is closer to the desired trajectory,the steady-state error is closer to zero,and the control parameters are fewer.