基于UIF-MPC仿真的UAV环航姿态控制研究

Research on Attitude Control of UAV Circumnavigation Based on UIF-MPC Simulation

为解决无人机(unmanned aerial vehicle,UAV)在算法结构冗杂和未知外部干扰的环境下控制系统操作难度大的问题,提出一种基于UIF-MPC融合的自适应全局快速终端滑模控制方法。考虑到在环境复杂、时间敏感及通信受限条件下给出UAV姿态运动观测模型;提出一种多控制变量交互的UIF-MPC融合滤波姿态算法,利用滤波器和PID控制器对模型不确定性和未知干扰进行补偿;根据UAV性能及饱和控制条件设定姿态设定控制参数并设定目标位置估计均方根误差,带入UIF-MPC模型并与传统单UIF模型进行比较。结果表明UIF-MPC融合模型可以较好融合系统需求,且在运动过程中具有较好的估计精度及机动控制的鲁棒性。

In order to solve the problem that the control system of Unmanned aerial vehicle(UAV)is difficult to operate in the environment of complex algorithm structure and unknown external interference,an adaptive global fast terminal sliding mode control method based on UIF-MPC fusion is proposed.Firstly,considering the complex environment,time sensitivity and limited communication conditions,the UAV attitude motion observation model is given;secondly,a UIF-MPC fusion filtering attitude algorithm with multi-control variable interaction is proposed.The filter and PID controller are used to compensate for the uncertainty and unknown interferences;finally,the attitude setting control parameters and root mean square errora of target position estimation are set according to the UAV performance and saturation control conditions,UIF-MPC model is introduced to make comparison with the traditional UIF model.The results show that the UIF-MPC fusion model can better integrate the system requirements,and has better estimation accuracy and robustness of maneuver control during the motion process.