基于IBSA的四旋翼无人机ADRC参数优化  

Optimization of Quadrotor UAV Active Disturbance Rejection Control Parameters Based on Improved Bird Swarm Algorithm

作　　者：陈城[1] 刘云平[1] 鲁倍辰 王爽[1] 方卫华[3] CHEN Cheng;LIU Yunping;LU Beichen;WANG Shuang;FANG Weihua(School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044,China;College of Computer Science and Software Engineering,Hohai University,Nanjing 210024,China;Nanjing Research Institute of Hydrology and Water Conservancy Automation,Ministry of Water Resources,Nanjing 210012,China)

机构地区：[1]南京信息工程大学自动化学院,江苏南京210044 [2]河海大学计算机与软件学院,江苏南京210024 [3]水利部南京水利水文自动化研究所,江苏南京210012

出　　处：《控制工程》2025年第3期535-544,共10页Control Engineering of China

基　　金：江苏省研究生科研与实践创新计划项目(KYCX24_1493);江苏省水利厅科技项目(2021073)。

摘　　要：针对多变量和强耦合的四旋翼无人机自抗扰控制器的参数多且难以整定优化等问题,提出了一种改进鸟群算法来整定优化四旋翼无人机自抗扰控制器的参数。首先,采用欧拉-庞卡莱方程建立模块化的符号数学模型,以提高四旋翼无人机的建模效率。其次,基于所建立的符号数学模型对其进行参数化。然后,将经典PID控制算法、自抗扰控制器算法、基于粒子群优化的自抗扰控制器参数优化算法以及基于改进鸟群算法的自抗扰控制器参数优化算法在四旋翼无人机的姿态稳定性、跟踪稳定性以及抗干扰稳定性等方面分别进行比较分析。最后,结果表明,基于改进鸟群算法的自抗扰控制器参数整定优化算法具有抗干扰性强、收敛速度快以及鲁棒性好等优势。To solve the problems that active disturbance rejection controller of quadrotor UAV with the multivariable and strongly coupled have many parameters and is difficult to tune and optimize,an improved bird swarm algorithm is proposed to tune and optimize the parameters of the active disturbance rejection controller of quadrotor UAV.Firstly,a modular symbolic dynamics model is established using the Euler-Poincare equation to improve the modeling efficiency of quadrotor UAV.Secondly,the model is parameterized based on the established symbolic mathematical model.Then,the classic PID control algorithm,the active disturbance rejection controller algorithm,the active disturbance rejection controller parameter optimization algorithm based on particle swarms algorithm,and the active disturbance rejection controller parameter optimization algorithm based on the improved bird swarm algorithm are compared and analyzed in terms of attitude stability,tracking stability and anti-interference stability of the quad-rotor UAV.Finally,the results show that the auto-disturbance rejection controller parameter tuning optimization algorithm based on the improved bird flock algorithm has the advantages of strong anti-disturbance,fast convergence speed and good robustness.

关 键 词：四旋翼无人机 鸟群算法 自抗扰控制器 稳定性 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]