计算机工程与应用Issue(1)：234-237,4.DOI:10.3778/j.issn.1002-8331.1306-0361
有色噪声条件下的子空间辨识改进方法及应用
Improved subspace identification method in presence of non-stationary noise and its application
摘要
Abstract
In order to deal with non-stationary noise in the industrial production processes, an improved subspace identifi-cation method is proposed. The identification result is not efficient in presence of non-stationary noise through traditional subspace identification method. So the transformational system model form is used to eliminate the effect of non-stationary noise on system through improved subspace identification method. The accurate state-space model is obtained through identification using the transformational system model data. Practice has proved, the state-space model is more suitable for industrial processes. CSTR is a typical industrial production system and the subspace identification method is applied to the process simulation on a CSTR. Through comparisons of the predication error before and after improved, the effec-tiveness of the proposed method is showed.关键词
有色噪声/子空间辨识/状态空间模型/连续搅拌反应釜(CSTR)Key words
non-stationary noise/subspace identification/state-space model/Continuous Stirred Tank Reactor(CSTR)分类
信息技术与安全科学引用本文复制引用
罗小锁,陈学昌,曹保山..有色噪声条件下的子空间辨识改进方法及应用[J].计算机工程与应用,2015,(1):234-237,4.基金项目
国家自然科学基金（No.61174059，No.60874046）。 （）
