Identification of frequency domain maximum likelihood system using genetic algorithm

被引：0

作者：

Duan, Shi-Zhong ^{[1
]}

Zhou, Yin-Qing ^{[1
]}

机构：

[1] Dept. of Electron. Eng., Beijing Univ. of Aero. and Astron., Beijing 100083, China

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2001年 / 27卷 / 05期

关键词：

Computer simulation - Genetic algorithms - Linear systems - Mathematical models - Maximum likelihood estimation - Parameter estimation;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Float point genetic algorithms were used to solve the start value and convergence problems of frequency domain maximum likelihood system identification, based on errors-in-variables model. Simulations showed that it is difficult to get accurate result only using the genetic algorithm, while the traditional non-linear iterative optimization methods may lead to convergence to local minimum in some cases. By taking the advantages and overcoming the defects of the above two methods, an improved algorithm was proposed which can give the start value of delay directly and can find the global minimum precisely within a rather short time, even when cost function has a lot of local minima. In addition, the improved algorithm exhibited broader adaptability than the old ones.

引用

页码：532 / 535

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