自适应变搜索域遗传算法及其在发动机模型中的应用

推进技术 ›› 2007, Vol. 28 ›› Issue (4): 428-432.

自适应变搜索域遗传算法及其在发动机模型中的应用

陈永琴,苏三买

西安电子科技大学机电工程学院;陕西西安710071;西北工业大学动力与能源学院陕西西安710072

发布日期:2021-08-15
基金资助:
航空推进技术验证计划项目资助(APTD-0901-13)

Adaptive variable search scope genetic algorithm and its application in aeroengine mathematical model

School of Electronic Mechanical Engineering,Xidian Univ.,Xi’an 710071,China;Coll.of Power and Energy,Northwestern Polytechnical Univ.,Xi’an 710072,China

Published:2021-08-15

摘要/Abstract

摘要： 针对发动机数学模型中非线性方程插值解法的不足,提出非线性方程自适应变搜索域遗传算法解法。论文详细分析了方程求解转化为遗传算法优化的数学描述、依据方程解临域特征的自适应变搜索域机理及算法的具体实现技术。实例计算与发动机仿真结果说明:所设计的变搜索域遗传算法可作为通用的非线性方程解法,相比较于简单遗传算法,能成倍提高计算效率;替代插值解法应用于发动机模型,可有效提高模型的收敛性。

关键词: 非线性方程+;遗传算法+;航空发动机;数学模型

Abstract: Aeroengine nonlinear mathematical model includes a group of similar nonlinear equation.Interpolation method now in use is not always effective due to initial value selection.In this paper,adaptive variable search scope genetic algorithm(AVSSGA) is put foreward to solve nonlinear equation.Algorithm model which converts nonlinear equation solution to genetic algorithm optimization and adaptive variable search scope method according as the solution neighborhood features of equation are analysed in detail.Real examples show that AVSSGA is a common solution for nonlinear equation,compared with simple genetic algorithm(SGA).It can double computing efficiency.When replaced interpolation method in aeroengine mathematical model with this algorithm,it can improve model convergence.

Key words: Nonlinear equation+;Genetic algorithm+;Aeroengine;Mathematical model

陈永琴,苏三买. 自适应变搜索域遗传算法及其在发动机模型中的应用[J]. 推进技术, 2007, 28(4): 428-432.