基于自适应多尺度超螺旋算法的无人机集群姿态同步控制

Attitude Consensus Control of UAV Swarm Based on Adaptive Multi-scale Super-twisting Algorithm

四旋翼无人机(Unmanned aerial vehicle, UAV)系统姿态角和角速度分别为运行在不同时间尺度上的慢、快动态.由于输入扰动的上界难以精确估计,本文提出一种基于自适应多尺度超螺旋(Super-twisting, STW)滑模算法的无人机集群一致性控制策略.首先,建立无人机集群系统的姿态角模型,并通过奇异摄动理论将其化为两时间尺度形式.基于系统的快慢特性,本文设计两时间尺度的超螺旋滑模算法,并采用自适应增益处理无人机集群系统的未知边界非线性.此外,还提出一种改进型自适应多尺度超螺旋滑模算法,进一步减少系统的一致性收敛时间,实现无人机集群姿态角有限时间内同步.最后通过仿真分析,验证两种自适应多尺度超螺旋算法的正确性和有效性.

In a UAV(unmanned aerial vehicle)system,the attitude angle and angular velocity of the UAV are,respectively,the slow and fast dynamics operating in different time scales.Due to the difficulty in the estimation of the bound of disturbance,this paper proposes a control method for UAV swarm,based on the adaptive multi-scale STW(super-twisting)sliding mode algorithm.First,the attitude model of the UAV swarm system is established,which is transformed into a two-time-scale model via singular perturbation theory.On this basis,this paper designs a two-time-scale STW sliding mode algorithm with adaptive gains to deal with the perturbations and unknows.Furthermore,by adding a few linear iterms,a modified adaptive STW control algorithm is also provided,which further reduces the convergence time and achieves the synchronization of the attitudes in finite time.Finally,the effectiveness of two different adaptive multi-scale STW algorithms are verified through simulations.