摘要
多智能体集群作战是未来战场的重要形式。作为集群作战中的关键技术,编队控制有着广泛的应用。以编队控制律为研究目标,选择2种优化控制方法:线性二次型调节器(linear quadratic regulator,LQR)方法和模型预测控制(model predictive control,MPC)方法。针对圆形编队轨迹,采用二阶动力学模型,基于相似一致性算法,在二维平面上仿真4个智能体绕轨迹中心旋转的编队运动场景,探究2种优化控制方法仿真效果。结果表明模型预测控制相比线性二次型调节器控制收敛速度更快,控制稳定性更高,侧向误差更小。增加侧向加速度补偿之后编队智能体在模型预测控制的作用下,圆形轨迹侧向追踪误差大幅度降低。
Multi-agent group combat is an important form in the future battlefield.As a key technology in group operations,formation control has a wide range of application.Focusing on the formation control law,two optimal control methods are applied:linear quadratic regulator(LQR)and model predictive control(MPC).The methods are analyzed in a circular formation scene.Based on the similarity consistency algorithm,utilizes second-order dynamic model to explore the optimal control effect of four agents rotating around the trajectory center in the two-dimension plane.The results show that the model predictive control has larger speed of convergence,higher control stability and smaller side errors than the linear quadratic regulator method.The lateral error of the formation agent following a circular trajectory is greatly reduced by MPC with lateral acceleration compensation.
作者
武梅丽文
王晓东
宋勋
陈燕飞
WU Mei-liwen;WANG Xiao-dong;SONG Xun;CHEN Yan-fei(Beijing Institude of Electronic System Engineering,Beijing 100854,China;First Military Representative Office of Air Force Equipment Department in Beijing,Beijing 100854,China)
出处
《现代防御技术》
北大核心
2021年第1期47-52,共6页
Modern Defence Technology
关键词
集群作战
编队控制
线性二次型控制
模型预测控制
相似一致性
时变编队
swarms warfare
formation control
linear quadratic regulator(LQR)
model predictive control(MPC)
Similarity consistency algorithm
time-varying control
