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联合估计稳态算法及其在过程辨识中的应用
引用本文:俞星星, 张大力, 阎平凡. 联合估计稳态算法及其在过程辨识中的应用. 自动化学报, 1998, 24(2): 217-220.
作者姓名:俞星星  张大力  阎平凡
作者单位:1.清华大学自动化系,北京
基金项目:国家攀登计划认知科学(神经网络)重大关键项目
摘    要:时滞和滤波联合估计问题是自适应系统建模和时滞估计两方面的交叉.本文针对先时滞后滤波的串联模型.提出基于快速横向滤波器的递推最小二乘算法,并以合成氨生产过程现场数据为例进行模型预测.仿真结果表明,这种结合时滞跟踪的自适应滤波器适于变时滞低阶系统建模.

关 键 词:时滞   联合估计   递推最小二乘   自适应滤波
收稿时间:1996-04-17

Joint Estimation Steady Algorithm and its Application to Process Identification
Yu Xingxing, Zhang Dali, Yan Pingfan. Joint Estimation Steady Algorithm and its Application to Process Identification. ACTA AUTOMATICA SINICA, 1998, 24(2): 217-220.
Authors:Yu Xingxing  Zhang Dali  Yan Pingfan
Affiliation:1. Department of Automation,Tsinghua University,Beijing
Abstract:In industry production processes, there are many serial systems of delay and filter.Joint identification of delay and filter is the cross research area of adaptive system modelingand time delay estimation. For the system model in which the input signal is first delayed andthen filtered, this paper develops a pre-delay tracking recursive least squares filtering algorithmbased on fast transversal filter realizations. The algorithm is applied to model predictionof a chemical industry process for synthetic ammonia, the simulation results justify that thiskind of delay tracking adaptive filter is suitable for low order and raring time delay systemmodeling.
Keywords:,Time delay,joint estimation, recursive least squares, adaptive filtering
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