典型文献
A multi-strategy pigeon-inspired optimization approach to active disturbance rejection control parameters tuning for vertical take-off and landing fixed-wing UAV
文献摘要：
In this paper,Active Disturbance Rejection Control(ADRC)is utilized in the pitch con-trol of a vertical take-off and landing fixed-wing Unmanned Aerial Vehicle(UAV)to address the problem of height fluctuation during the transition from hover to level flight.Considering the dif-ficulty of parameter tuning of ADRC as well as the requirement of accuracy and rapidity of the controller,a Multi-Strategy Pigeon-Inspired Optimization(MSPIO)algorithm is employed.Particle Swarm Optimization(PSO),Genetic Algorithm(GA),the basic Pigeon-Inspired Optimization(PIO),and an improved PIO algorithm CMPIO are compared.In addition,the optimized ADRC control system is compared with the pure Proportional-Integral-Derivative(PID)control system and the non-optimized ADRC control system.The effectiveness of the designed control strategy for forward transition is verified and the faster convergence speed and better exploitation ability of the proposed MSPIO algorithm are confirmed by simulation results.
文献关键词：
中图分类号：
作者姓名：
Hangxuan HE;Haibin DUAN
作者机构：
State Key Laboratory of Virtual Reality Technology and Systems,Beiliang University,Beijing 100191,China;Peng Cheng Laboratory,Shenzhen 518000,China
文献出处：
引用格式：
[1]Hangxuan HE;Haibin DUAN-.A multi-strategy pigeon-inspired optimization approach to active disturbance rejection control parameters tuning for vertical take-off and landing fixed-wing UAV)[J].中国航空学报（英文版）,2022(01):19-30
A类：
hover,MSPIO,CMPIO
B类：
multi,strategy,pigeon,inspired,optimization,approach,active,disturbance,rejection,parameters,tuning,vertical,take,off,landing,fixed,wing,UAV,this,paper,Active,Disturbance,Rejection,Control,ADRC,utilized,pitch,Unmanned,Aerial,Vehicle,address,problem,height,fluctuation,during,transition,from,level,flight,Considering,dif,ficulty,well,requirement,accuracy,rapidity,controller,Multi,Strategy,Pigeon,Inspired,Optimization,algorithm,employed,Particle,Swarm,PSO,Genetic,Algorithm,GA,basic,improved,compared,addition,optimized,system,pure,Proportional,Integral,Derivative,PID,effectiveness,designed,forward,verified,faster,convergence,speed,better,exploitation,ability,proposed,confirmed,by,simulation,results
AB值：
0.573003
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