无人机自驾仪自适应控制系统的设计与仿真

Design and Simulation of UAV's Autopilot Adaptive Control System

针对某无人机的控制问题,为了找出一种比PID更适合的控制方法,提出了一种基于模糊神经网络(FNN))的模型参考自适应方法,并设计了相应的双通道控制律,对无人机纵向运动中的速度和俯仰角进行控制。应用所提出的方法,对某无人机纵向运动的控制问题进行了研究。仿真结果表明,与传统的PID控制相比较,FNN的模型参考自适应控制算法具有较快的收敛速度和较小的稳态误差,并能够消除无人机纵向运动中存在的耦合。

The problem of UAV＇s longitudinal motion control was studied. To improve the dynamic response and the steady state performance of the control system, the model reference adaptive control method based on the fuzzy neural network was proposed, and the corresponding two - channel control law was designed, which controls the velocity and pitch rate. The simulation results show, compared with the PID control law, the model reference adaptive control method based on the FNN has fast convergence rate and smaller steady - state error, and eliminates the coupling which exists in the UAV＇s longitudinal motion.