本文選題：極大似然辨識 + 信息濾波��； 參考：《江南大學》2017年博士論文

【摘要】：由于工業(yè)生產過程受到多種因素的干擾,使得有色噪聲干擾系統(tǒng)的辨識變得更加困難.論文通過極大化似然函數,結合信息濾波技術研究一類有色噪聲線性系統(tǒng)和非線性系統(tǒng)的參數辨識問題,選題具有理論意義和應用前景.取得了如下的成果.(1)針對標量方程誤差ARMA系統(tǒng),提出了基于信息濾波的極大似然增廣梯度算法;為了加快梯度算法的收斂速度,引進新息,提出了基于信息濾波的極大似然多新息增廣梯度算法.為了提高參數估計精度,推導了基于信息濾波的極大似然增廣最小二乘算法.進一步,將提出的算法推廣到多變量方程誤差ARMA系統(tǒng)的參數估計中.(2)針對類多變量受控自回歸ARMA系統(tǒng),由于多變量系統(tǒng)的變量多、維數大,將系統(tǒng)分解成m(m是系統(tǒng)輸出的維數)個子系統(tǒng),再利用信息濾波對每個子系統(tǒng)的輸入輸出數據進行濾波,提出了子系統(tǒng)的信息濾波極大似然增廣梯度算法,并與極大似然廣義增廣梯度算法進行比較,減少了有色噪聲對參數估計的影響,提高了參數辨識精度.(3)針對多輸入非線性Box-Jenkins系統(tǒng),為了解決其非線性及有色噪聲干擾的困難,利用分解技術,研究了基于分解的極大似然廣義增廣最小二乘辨識算法;針對有色噪聲的干擾,選取適當的濾波器,對系統(tǒng)的輸入輸出數據進行預處理,再結合極大似然方法,提出了基于信息濾波技術的極大似然廣義增廣梯度辨識算法,減少了參數估計誤差.論文中,對所提出的辨識算法都結合了數值算例,進行了仿真試驗,通過仿真例子驗證了算法的有效性。
[Abstract]:Due to the interference of many factors in the industrial production process, it is more difficult to identify the colored noise jamming system. In this paper, the problem of parameter identification for a class of linear and nonlinear systems with colored noise is studied by means of maximum likelihood function and information filtering technique. The following results are obtained: (1) aiming at the scalar equation error ARMA system, a maximum likelihood augmented gradient algorithm based on information filtering is proposed, and in order to speed up the convergence of the gradient algorithm, new information is introduced. A maximum likelihood multi-innovation augmented gradient algorithm based on information filtering is proposed. In order to improve the accuracy of parameter estimation, a maximum likelihood augmented least square algorithm based on information filtering is derived. Furthermore, the proposed algorithm is extended to the parameter estimation of multivariable equation error ARMA system. (2) for multivariable controlled autoregressive ARMA system, because the multivariable system has many variables and large dimension, The system is decomposed into three subsystems, which are the dimension of the system output. Then the input and output data of each subsystem are filtered by information filtering, and the information filtering maximum likelihood augmentation gradient algorithm of the subsystem is proposed. Compared with the maximum likelihood generalized augmented gradient algorithm, the influence of colored noise on parameter estimation is reduced, and the accuracy of parameter identification is improved. For the multi-input nonlinear Box-Jenkins system, it is difficult to solve the nonlinear and colored noise disturbance. Using decomposition technology, the maximum likelihood generalized augmented least square identification algorithm based on decomposition is studied, and the appropriate filter is selected to pre-process the input and output data of the system, and then the maximum likelihood method is combined with the maximum likelihood method. A maximum likelihood generalized augmented gradient identification algorithm based on information filtering technique is proposed to reduce the error of parameter estimation. In this paper, the proposed identification algorithms are combined with numerical examples, and the effectiveness of the algorithm is verified by simulation examples.
【學位授予單位】：江南大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：N945.14

【參考文獻】

中國期刊全文數據庫 前10條

1 丁鋒;徐玲;劉喜梅;;信號建模(3):多頻信號模型的遞推參數估計[J];青島科技大學學報(自然科學版);2017年03期

2 丁鋒;徐玲;劉喜梅;;信號建模(2):雙頻率信號[J];青島科技大學學報(自然科學版);2017年02期

3 丁鋒;徐玲;劉喜梅;;信號建模(1):單頻率信號[J];青島科技大學學報(自然科學版);2017年01期

4 孫海洋;張利;;無人機跟蹤場景下的粒子濾波算法的改進[J];計算機仿真;2017年02期

5 陳亞靜;蔡如華;吳孫勇;桂叢楠;;基于粒子濾波的股價預測方法[J];統(tǒng)計與決策;2017年03期

6 肖震宇;于舒春;劉爽;于曉洋;;基于改進維納濾波的運動模糊儀表圖像恢復算法[J];電測與儀表;2017年02期

7 丁鋒;汪菲菲;;損失數據線性參數系統(tǒng)的遞推最小二乘辨識方法[J];控制與決策;2016年12期

8 蔡磊;王艷;紀志成;;基于折息遞推辨識算法的數控機床能效預測[J];系統(tǒng)仿真學報;2016年08期

9 丁鋒;;系統(tǒng)辨識算法的復雜性、收斂性及計算效率研究[J];控制與決策;2016年10期

10 劉艷君;丁鋒;;多變量系統(tǒng)的耦合梯度辨識算法與性能分析[J];控制與決策;2016年08期

中國博士學位論文全文數據庫 前1條

1 李俊紅;極大似然辨識方法的研究[D];江南大學;2013年

，

本文編號：1880460