基于NMPC-PID的无人机控制算法  

Control algorithm for QUAV based on NMPC-PID

作　　者：谭惠东 李天松[1] 莫雄 卢艳菊 严一超 TAN Huidong;LI Tiansong;MO Xiong;LU Yanju;YAN Yichao(School of Information and Communication Engineering,Guilin University of Electronic Technology,Guilin 541004,China)

机构地区：[1]桂林电子科技大学信息与通信工程学院,广西桂林541004

出　　处：《桂林电子科技大学学报》2020年第3期195-200,共6页Journal of Guilin University of Electronic Technology

基　　金：国家自然科学基金(61771150);广西自然科学基金(0832012)。

摘　　要：针对无人机控制性能易受风扰影响的情况,设计了一种非线性预测PID控制算法。建立无人机高度与姿态角直接受PID参数控制的动力学模型,采用NNI与NNC复合神经网络对下一时刻无人机所受荷载进行非线性预测,并设计了NMPC-PID控制算法。仿真结果表明,相较于传统PID控制算法,NMPC-PID控制算法在鲁棒性、抗干扰能力方面具有明显优势。实际风扰情况下无人机悬停实验数据分析表明,采用NMPC-PID控制算法的无人机具有能够适应风速变化的特点。A nonlinear predictive PID control algorithm is designed for the situation that the drone control performance is susceptible to wind disturbance.Firstly,the dynamic model of drone height and attitude angle directly controlled by PID parameters is established.Secondly,the NNI and NNC composite neural network is used to predict the load of the UAV at the next moment and the NMPC-PID control algorithm is designed.The comparison simulation shows that compared with the traditional PID control algorithm,the NMPC-PID control algorithm has obvious advantages in robustness and anti-interference ability.The analysis of the experimental data of the UAV hovering under actual wind disturbance shows that the UAV adopting the NMPC-PID control algorithm has the characteristics of being able to adapt to the wind speed change.

关 键 词：非线性预测控制 动态递归神经元 四旋翼无人机 

分 类 号：TD324[矿业工程—矿井建设]