机载LiDAR姿态角稳定装置的神经网络逆系统解耦控制研究

Decoupling Control of Attitude Stabilization Device for Airborne LiDAR Based on Neural Network Inverse System

机载激光雷达(LiDAR)工作过程中,机载平台姿态角波动会造成激光扫描点云的密度分布不均匀,导致后续数字表面模型重建时精度降低,因此设计了一种推转式姿态角稳定装置,可实现机载平台姿态角波动的实时补偿。设计的姿态角稳定装置具有非线性和强耦合的运动控制特点,为消除其运动耦合关系、提高运动控制精度,基于神经网络逆系统解耦控制策略对姿态角稳定装置进行解耦处理,取得了满意的控制效果。首先,建立了姿态角稳定装置动力学系统的多变量神经网络逆系统模型;其次,采用PID闭环反馈控制器与神经网络逆系统前馈补偿器组合的前馈-反馈复合控制器,实现控制系统的实时解耦,改善动态控制性能;最后,进行了实验验证。结果表明,设计的神经网络逆系统解耦控制方法可有效提高姿态角稳定装置控制精度,并对误差干扰具有优良鲁棒性。

During the operation of airborne LiDAR,the attitude changes of airborne platform can significantly influence the density distribution of point cloud and the accuracy of the reconstructed Digital Surface Model(DSM),so an attitude stabilization device is designed to compensate for them in real time.The designed attitude stabilization device is a nonlinear and strong coupling system.In order to eliminate the coupling effect of the attitude stabilization device and improve its motion control accuracy,a decoupling control strategy based on neural network inverse system is proposed,which obtains satisfying control effects.Firstly,the multi-variable neural network inverse model for dynamics system of the attitude stabilization device is established.Then,a PID closed-loop feedback controller and a feedforward compensator of neural network inverse system are composed to be a feedforward-feedback compound controller,to decouple the control system in real time and to improve the dynamic control performance.Finally,the decoupling control system is testified.The experimental results show that the designed decoupling control method based on neural network inverse system effectively improves the control accuracy of the attitude stabilization device,and has excellent robustness for error interference.