基于状态空间MPC的无人机无人车联合运动控制

Cooperative Formation Control for Unmanned Aerial Vehicles and Unmanned Ground Vehicles Based on State Space Model Predictive Control

针对四旋翼无人机无人车联合运动缺乏对系统成员姿态约束的问题,研究了一种基于模型预测控制(MPC)的分布式联合运动控制方法。基于虚拟结构法,使用虚拟领航者策略,以虚拟领航者提供参考轨迹及参考速度,分别在各无人器平台上转换成各自所需的预测时域信息,结合推导的各无人器的状态空间模型滚动优化实现预测控制。限定四旋翼高度方向运动状态与偏航角,构造以俯仰角、横滚角与重力加速度乘积为位置运动输入的状态空间模型,将无人机内环姿态控制约束加入位置运动,增强飞行稳定性。改良无人车状态空间模型,增加速度信息得到可提供位置速度追踪的增广状态空间模型,增强运动追踪能力。仿真表明在满足无人器姿态约束条件下,能够保证联合运动的位置速度精度。

A distributed formation motion control method based on model predictive control is designed to solve the coopera⁃tive formation control problem of four-rotor UAV and two-wheel differential sports unmanned vehicles.This paper uses the lead⁃er-follower method to provide reference trajectories through virtual pilots.According to the formation requirements,the nonlinear mo⁃tion models of UAVs and unmanned vehicles are appropriately changed to obtain a state space prediction model that meets the actual formation requirement.In order to better meet the actual engineering requirements,the constraint of the attitude control of the inner ring of the quadrotor UAV is added to the outer ring position motion control algorithm.The paper changes the traditional state predic⁃tion model of unmanned vehicles and obtain an augmented prediction model that can provide position velocity tracking.Finally,the simulation results show that the control effect of the method designed in this paper can meet the actual formation needs.