四旋翼无人机编队变换能耗优化仿真教学  

Simulated teaching for energy consumption optimization in quadcopter unmanned aerial vehicle formation change

作　　者：黄捷 李泽毅[1,2] HUANG Jie;LI Zeyi(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China;5G+Industrial Internet Institute,Fuzhou University,Fuzhou 350108,China)

机构地区：[1]福州大学电气工程与自动化学院,福建福州350108 [2]福州大学5G+工业互联网研究院,福建福州350108

出　　处：《实验技术与管理》2024年第4期102-108,共7页Experimental Technology and Management

基　　金：福建省本科高校教育教学研究项目(FBJY20230052)。

摘　　要：针对四旋翼无人机编队变换能耗优化仿真教学,该文以多无人机编队切换应用中存在无人机能耗不平衡的案例作为典型教学内容,提出了基于无人机编队能耗优化的仿真教学模式,设计了无人机集群编队队形变化能耗最优仿真教学总体方案,阐明各个无人机无碰撞地驶向目标点的实现思路。搭建的仿真教学实例有效地解决了无人机编队飞行时间短的问题。此设计已经用于研究生“无人机控制技术”的课程教学,可激发学生在传统算法上进行优化的创新思维。[Objective]The course content for unmanned aerial vehicle(UAV)control technology is extensive and complex,encompassing a broad spectrum of theoretical knowledge from various disciplines.It involves strong mathematical logic relationships and many formula derivations.The traditional teaching method,however,has proven to be inadequate in cultivating students’innovative and critical thinking abilities,resulting in disappointing academic results.Therefore,the challenge and focus of this course lie in discovering an effective teaching strategy.One that encourages each student’s active participation and provides them with opportunities to demonstrate their understanding and skills.To cultivate the students’problem-solving abilities within the context of UAV control courses,it is imperative to stimulate their creative thinking.This can be achieved through research guidance on course design and by implementing simulation teaching research on UAV formation energy consumption optimization.[Methods]The concept of multidrone formation switching presents unique challenges.Existing solutions,such as the Hungarian algorithm,can solve the assignment problem of the optimal total switching distance assignment.However,these solutions often result in certain UAVs being assigned excessively long flight paths or individual UAVs being tasked with high climbs.This invariably leads to higher power consumption during flight than during hovering,causing a rapid decrease in power consumption during formation switching.The outcome is a shorter flight time for the entire formation compared to other UAVs.To this end,we have refined the allocation plan.Our goal is to ensure that the flight paths of the UAVs during the formation switching process are similar and the flight times to the target waypoints are consistent,thereby avoiding the above problems.In this context,we employ the particle swarm optimization(PSO)algorithm to design the flight distance and climbing distance costs for the UAVs.We set an appropriate objective function and so

关 键 词：编队队形变换 能耗优化 仿真教学 无人机编队 

分 类 号：TP202.7[自动化与计算机技术—检测技术与自动化装置]