火力与指挥控制2026，Vol.51Issue(3)：74-80,7.DOI:10.3969/j.issn.1002-0640.2026.03.010
基于改进SA-PSO算法的飞机气动参数辨识算法
An Aerodynamic Parameter Identification Algorithm for Aircraft Based on the Improved SA-PSO Algorithm
摘要
Abstract
A novel maximum likelihood aerodynamic parameter identification algorithm based on improved Simulated Annealing-Particle Swarm Optimization(SA-PSO)is proposed to address the issue of aircraft dynamics analysis under uncertain aerodynamic parameters.This algorithm overcomes the sensitivity of the traditional Newton-Raphson algorithm to initial values when solving maximum likelihood problems.Moreover,a dynamic weight strategy is employed to enhance the global optimization performance of the PSO algorithm.The Metropolis Criterion from the SA algorithm is incorporated to improve the individual and global optimal update strategies of the PSO algorithm,effectively mitigating the premature convergence commonly observed in traditional PSO algorithms.Simulation results demonstrate that the proposed algorithm exhibits superior global search capabilities and achieves higher accuracy in parameter identification compared to both the standard PSO and Newton-Raphson algorithms.关键词
气动参数辨识/粒子群算法/极大似然算法/SA算法/Metropolis准则Key words
aerodynamic parameter identification/particle swarm optimization algorithm/maximum likelihood algorithm/simulated annealing algorithm/Metropolis criterion分类
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张磊磊,曾涛,秦林烽,罗一鸣,王锐,邢小军..基于改进SA-PSO算法的飞机气动参数辨识算法[J].火力与指挥控制,2026,51(3):74-80,7.基金项目
专项支撑科研资助项目(KY2022014) （KY2022014）
