摘要
针对传统人工势场(Artificial Potential Field,APF)解决避障问题时出现的局部极小值、目标不可达等缺点,提出了一种结合APF和具有协同避障效果的最优一致性控制方法。基于固定无向通信拓扑的双积分器无人机编队模型,引入具有避障代价函数的最优一致性控制协议,解决APF避障的局限性问题,同时对多无人机进行编队控制,使无人机编队控制系统的一致性性能指标、控制消耗性能指标和避障性能指标达到最优解。此外,通过对每架无人机构建虚拟斥力势场,防止在避障过程中出现机间碰撞。仿真结果表明,与改进APF的非最优一致性控制相比,本文提出的改进APF的最优一致性控制能够缩短任务用时32%,且能够极大程度上保持队形完整性,减少避障所造成的一致性消耗和控制损耗。
Aiming at the shortcomings of traditional artificial potential field(APF)for solving obstacle a⁃voidance problems,such as local minimum value and unreachable target,an optimal consensus control method taking advantage of obstacle avoidance effect and combination with APF is proposed.Based on the double integrator UAVs formation model with fixed undirected communication topology,the optimal consen⁃sus control protocol with obstacle avoidance cost function is introduced to solve the limitation of APF obstacle avoidance.At the same time,the formation control of multiple UAVs is developed to make the consensus per⁃formance index,control consumption performance index and obstacle avoidance performance index of UAVs formation control system reach the optimal solution.In addition,by establishing a virtual repulsion poten⁃tial field for each UAVs,the collisions among the UAVs during the obstacle avoidance process are prevented.The simulation results show that compared with the non⁃optimal consistency control of the improved APF,the optimal consistency control of the improved APF proposed can shorten the task time by 32%and can greatly maintain the integrity of the formation and reduce the consistency consumption and control loss caused by obstacle avoidance.
作者
李亚文
张鹏飞
何印
马振华
LI Yawen;ZHANG Pengfei;HE Yin;MA Zhenhua(School of Aerospace Engineering,North University of China,Taiyuan 030051,China;Research Institute of Intelligent Weapons,North University of China,Taiyuan 030051,China)
出处
《航天控制》
CSCD
2024年第1期17-23,共7页
Aerospace Control
基金
山西省基础研究计划资助项目(202103021224182)
山西省基础研究计划资助项目(202103021224187)。
关键词
无人机编队
协同避障
人工势场法
最优一致性控制
UAVs formation
Collaborative obstacle avoidance
Artificial potential field
Optimal consen⁃sus control
