您的位置:首页  > 论文页面

基于改进遗传算法的非线性仪表的参数辨识

发表时间:2008-05-31  浏览量:1847  下载量:784
全部作者: 李雅梅,杨飞霞
作者单位: 辽宁工程技术大学电气与控制工程学院
摘 要: 本文分析了节流式流量仪表的非线性及其导致计算结果的偏差,建立了仪表的非线性模型。针对标准遗传算法(simple genetic algorithm,SGA)收敛速度慢、易早熟等缺陷,提出了一种基于最优个体保留和自适应温度等策略的改进遗传算法。在此基础上将改进的遗传算法应用于非线性仪表的参数辨识,仿真结果证明改进后的遗传算法有更好的全局寻化和快速收敛能力。本文建立的非线性仪表参数辨识的方法,对提高火电厂主蒸汽流量在线计算的准确性,具有重要意义。
关 键 词: 自动控制技术;参数辨识;遗传算法;主蒸汽流量;非线性仪表
Title: Parameters identification of nonlinear apparatus based on an improved genetic algorithm
Author: LI Yamei, YANG Feixia
Organization: Institute of Electrical and Control Engineering, Liaoning Technical University
Abstract: The nonlinear property of flow-meter and the error caused by it are analyzed and the nonlinear model for flow-meter is established. To solve the defects of simple genetic algorithm(SGA) such as slow convergence and being subject to pre-maturity, an improved genetic algorithm is proposed, which includes many strategies, like reserving the best individuals and adopting self-adaptive temperature. By applying this modified genetic algorithm to the parameters identification of non-linear flow-meter, comparison results show that the improved algorithm has better global optimal ability and faster convergence ability. Based on parameters identification of nonlinear apparatus, the paper has provided an accurate and convenient method for the on-line calculating of main steam flow, and thus has significant meaning during actual production in power plant.
Key words: automatic control technology; parameters identification; genetic algorithm; main steam flow; nonlinear apparatus
发表期数: 2008年9月第10期
引用格式: 李雅梅,杨飞霞. 基于改进遗传算法的非线性仪表的参数辨识[J]. 中国科技论文在线精品论文,2008,1(10):1207-1212.
 
0 评论数 0
暂无评论
友情链接