首页 | 本学科首页   官方微博 | 高级检索  
     检索      

非线性随机系统的参数辨识及动态预报
引用本文:褚东升,赵平溪,刘希华,杨广雪.非线性随机系统的参数辨识及动态预报[J].中国海洋大学学报(自然科学版),1997(2).
作者姓名:褚东升  赵平溪  刘希华  杨广雪
作者单位:青岛海洋大学工程学院,胜利油田纯梁采油厂
基金项目:中国石油天然气总公司“九五”攻关课题资助
摘    要:鉴于含有加性噪声的指数模型描述了一类重要的非线性随机系统。本文给出这类系统的参数递推辨识算法,克服了迭代算法不能在线运行、需反复矩阵求逆的不足。当系统时变时,还采用了虚拟噪声技术来补偿因参数时变引起的建模误差,从而改善动态预报器的性能。应用这种方法,对油田采油井、注水井的套管损坏情况进行了多步动态预报,其精度令人满意

关 键 词:非线性系统  指数模型  加性噪声  参数辨识  套管损坏  动态预报

PARAMETER IDENTIFICATION FOR NONLINEAR STOCHASTIC SYSTEMS AND DYNAMIC PREDICTION
Chu Dongsheng,Zhao Pingxi,Liu Xihua,Yang Guanglei.PARAMETER IDENTIFICATION FOR NONLINEAR STOCHASTIC SYSTEMS AND DYNAMIC PREDICTION[J].Periodical of Ocean University of China,1997(2).
Authors:Chu Dongsheng  Zhao Pingxi  Liu Xihua  Yang Guanglei
Institution:Chu Dongsheng 1 Zhao Pingxi 2 Liu Xihua 2 Yang Guanglei 2
Abstract:The exponential models with additive noise describe a class of important nonlinear stochastic systems. This paper presents a recursive parameter identification algorithm for the system. Compared with the iterative algorithm, it can avoid the matrix inversion and can be operated on-line. When the system is time-varying, a fictitious noise technique is used to compensate the modeling error caused by the time-varying parameters, which can improve the performence of the dynamic predictor. Practical utility of the approach is illustrated by modeling and predicting the casing collapse rate of oil and intake wells for an oil field.The calculation result is satisfactory.
Keywords:nonlinear system  exponential model  additive noise  parameter identification  casing collapse  dynamic prediction
本文献已被 CNKI 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号