基于遗传算法的非线性系统状态空间辨识

基金项目: 国家自然科学基金（69974043）；国家博士点基金（99053317）；湖南省自然科学基金（99JJY20062）资助

详细信息

STATE-SPACE IDENTIFICATION FOR NONLINEAR SYSTEMS BASED ON GENETIC ALGORITHM

1.
Department of Automatic Control, Beijing Institute of Technology, Beijing 100081
2.
College of Information Science and Engineering, Central South University, Changsha 410083

摘要: 本文提出了一种基于遗传算法用状态空间方程描述非线性系统的辨识方法，研究表明遗传算法能克服此类系统不能采用传统最小二乘法辨识的困难，并能有效地辨识出状态空间维数及非线性度都不高的系统，同时指出基于遗传算法的非线性状态空间辨识方法在状态维数确定、关键项确定和非关键项删除等方面还有待进一步研究．
- 非线性系统 /
- 状态空间方程 /
- 系统辨识 /
- 遗传算法
Abstract: A nonlinear state-space identification method based on genetic algorithm has been proposed in this paper. It is shown that the problem of such systems that cannot be identified by classical least-square has been solved by genetic algorithms and perfect nonlinear state-space identification results can be obtained when the dimension of state and the nonlinear degree are low. Meanwhile, it has been pointed out that state dimension confirmation, significant term selection and insignificant term deletion in this method still need to be researched further.
- nonlinear systems /
- state-space equations /
- system identification /
- genetic algorithms

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