南京师范大学学报：工程技术版
南京師範大學學報：工程技術版
남경사범대학학보：공정기술판
Journal of Nanjing Nor Univ: Eng and Technol
2012年
2期
7-10
,共4页
贝叶斯推理模型%非线性系统%时变%监测
貝葉斯推理模型%非線性繫統%時變%鑑測
패협사추리모형%비선성계통%시변%감측
Bayesian inferring model%nonlinear system%time-variant%monitoring
提出了采用贝叶斯推理模型BIM（Bayesianinferringmodel）对时变非线性系统的输出进行在线监测的实现思路和方法．首先描述了时变非线性系统的在线输出监测问题．然后介绍了BIM结构和训练方法，BIM的特点在于训练样本完全采自于在线闭环系统，采用改进的觅食优化算法IEFOA（ImprovedE．ColiForagingOptimizationAlgorithm）离线训练门槛矩阵参数D．而在线预测应用时，采用滑动窗口数据实时更新BIM结构，从而实时跟踪系统的输出变化．最后，利用时变非线性对象对BIM的在线观测能力进行了验证，仿真结果表明BIM适合于系统的输出监测，并且具有设计简单、跟踪性能好等优点，为非线性系统的性能评估提供了一种新的底层数据预测方法．
提齣瞭採用貝葉斯推理模型BIM（Bayesianinferringmodel）對時變非線性繫統的輸齣進行在線鑑測的實現思路和方法．首先描述瞭時變非線性繫統的在線輸齣鑑測問題．然後介紹瞭BIM結構和訓練方法，BIM的特點在于訓練樣本完全採自于在線閉環繫統，採用改進的覓食優化算法IEFOA（ImprovedE．ColiForagingOptimizationAlgorithm）離線訓練門檻矩陣參數D．而在線預測應用時，採用滑動窗口數據實時更新BIM結構，從而實時跟蹤繫統的輸齣變化．最後，利用時變非線性對象對BIM的在線觀測能力進行瞭驗證，倣真結果錶明BIM適閤于繫統的輸齣鑑測，併且具有設計簡單、跟蹤性能好等優點，為非線性繫統的性能評估提供瞭一種新的底層數據預測方法．
제출료채용패협사추리모형BIM（Bayesianinferringmodel）대시변비선성계통적수출진행재선감측적실현사로화방법．수선묘술료시변비선성계통적재선수출감측문제．연후개소료BIM결구화훈련방법，BIM적특점재우훈련양본완전채자우재선폐배계통，채용개진적멱식우화산법IEFOA（ImprovedE．ColiForagingOptimizationAlgorithm）리선훈련문함구진삼수D．이재선예측응용시，채용활동창구수거실시경신BIM결구，종이실시근종계통적수출변화．최후，이용시변비선성대상대BIM적재선관측능력진행료험증，방진결과표명BIM괄합우계통적수출감측，병차구유설계간단、근종성능호등우점，위비선성계통적성능평고제공료일충신적저층수거예측방법．
The implementation idea and solution are proposed in this article for the output on-line monitoring of the time- variant nonlinear system by using bayesian inferring model （BIM）. Firstly, the on-line monitoring problem of nonlinear system is described. Then the BIM structure and training methods are introduced. The characteristics of the BIM include that the sample data for off-line training are from the closed loop system and the optimization algorithm for the threshold matrix D is selected as the improved foraging optimization algorithm （ IEFOA ）. While in the on-line applications, the sliding window data are used to update the structure of the BIM for the on-line tracing of the system output. The time-va- riant nonlinear object is employed to validate the on-line monitoring ability of the BIM. The simulation results indicate that the BIM is adapted to the system on-line output monitoring and owns the characteristics of easy design, high accuracy tracing ability and etc, which provide a kind of data prediction method for the lowest system.
