摘要
针对多源不确定强耦合下的四旋翼无人机姿态控制问题,首次设计了一种多层逼近自适应神经网络动态面控制算法。区别于以往的加性耦合不确定研究,考虑无人机飞行控制中的乘性耦合多源不确定估计与补偿问题。首先,构建不确定四旋翼无人机姿态动力学模型,并基于神经网络与傅里叶展开实现乘性耦合不确定的巧妙转换;其次,将自适应技术与反步法相结合,设计多层逼近自适应控制律;同时将动态面技术用于解决反步法中虚拟控制律求导问题。完整理论分析与仿真实验表明了所述控制策略的有效性。
A dynamic surface control algorithm based on multi-layer adaptive neural network is proposed for the attitude control problem of the quadrotor UAV with multi-source strong coupling uncertainties for the first time.Different from the previous research on additive coupling uncertainties,the problem of multi-source multiplicative uncertainties estimation and compensation in UAV flight control is considered.First of all,a four-rotor UAV attitude dynamics model with multiplicative strong coupling uncertainties is constructed,and the uncertainties are ingeniously converted based on neural network and Fourier expansion.Secondly,a multi-layer approximation adaptive control law is designed based on the combination of adaptive technology and backstepping method.At the same time,dynamic surface technology is used to solve the derivation problem of virtual control law in the backstepping method.The effectiveness of the proposed control strategy is proved through complete theoretical analysis and simulation experiments.
作者
刘晨阳
吴大伟
郭一泽
吕欣赛
周佳妮
邵书义
LIU Chenyang;WU Dawei;GUO Yize;LV Xinsai;ZHOU Jiani;SHAO Shuyi(School of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China;College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《航空学报》
EI
CAS
CSCD
北大核心
2023年第S01期150-159,共10页
Acta Aeronautica et Astronautica Sinica
基金
国家自然科学基金(62103135)
中央高校基本科研业务费专项资金(B210202068)
