On identification of Volterra kernels of nonlinear systems by separating kernel slices

非线性系统Volterra核分离核片辨识

• 批准号: 14550449
• 负责人: KASHIWAGI Hiroshi
• 金额: $ 1.79万
• 依托单位: Kumamoto University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2002
• 资助国家: 日本
• 起止时间: 2002 至 2003
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-14550449/
• 关键词: Nonlinear system; Identification; Volterra kernel; M-sequence; Correlation technique; Model Predictive Control; Process control; M系列; 非形システム; 信号処理; 相関法

The authors have recently developed a new method for obtaining Volterra kernels of nonlinear system by use of a pseudorandom M-sequence. In this method, the most important problem is how to separate overlapped kernel slices which appear in the crosscorrelation. The authors have investigated two methods for separating those kernel slices : one is the suitable selection of M-sequence, and the other is amplitude variation method. We have obtained the following results.(1)On considering the fact that when the amplitude of the input M-sequence is changed, the amplitude of the output from n'th order Volterra kernel varies, we have obtained the method for separating overlapped Volterra kernel slices. The simulation shows that this method is useful.(2)This method is applied to a chemical process, and the result was presented at AdCONIP held in Kumamoto in June 2002.(3)This method was also presented at APCCM'2000 held in Dali, China in August 2002.(4)The general idea of identification of nonlinear system is presented at ICSE held in Coventry, UK, in September 2003.(5)This method is applied to Nonlinear Model Predictive Control, and the results are presented at ICCAS'03 held in Gyoungju, Korea, in October 2003.(6)The application of this method to Nonparametric Nonlinear Model Predictive Control appeared in Krean J.Chem.Eng. in 2004This method is considered to be widely usable in nonlinear industrial control systems.

作者最近发展了一种利用伪随机M序列获得非线性系统沃尔泰拉核的新方法。在该方法中，最重要的问题是如何分离互相关中出现的重叠核切片。本文研究了两种分离核切片的方法：一种是选择合适的M序列，另一种是振幅变化法。我们得到了以下结果。(1)On考虑到当输入M序列的幅值变化时，n阶沃尔泰拉核的输出幅值也会变化，得到了分离重叠沃尔泰拉核切片的方法。仿真结果表明该方法是有效的。（2）将该方法应用于化学过程，并于2002年6月在熊本举行的AdCONIP上发表了结果。（3）2002年8月在中国大理举行的亚太经合组织2000年年会上也介绍了这一方法。（4）2003年9月在英国考文垂召开的国际非线性工程师大会上，介绍了非线性系统辨识的基本思想。（5）将该方法应用于非线性模型预测控制，并于2003年10月在韩国光州举行的ICCAS'03上发表了结果。（6）2004年Krean J.Chem.Eng.发表了该方法在非参数非线性模型预测控制中的应用。

项目成果

H.Kashiwagi, H.Harada, L.Rong: "Identification of Third Order Volterra Kernels of Nonlinear Cfhemical Processes"Proc. AdCONIP held in Kumamoto, Japan. 411-416 (2002)

H.Kashiwagi，H.Harada，L.Rong：“非线性化学过程的三阶 Volterra 核的识别”Proc。

H.Kashiwagi, Y.Li: "Nonparametric Nonlinear Model Predictive Control"Proc.ICCAS held in Gyoungju, Korea. 1443-1448 (2003)

H.Kashiwagi、Y.Li：“非参数非线性模型预测控制”Proc.ICCAS 在韩国庆州举行。

H.Kashiwagi, H.Harada, L.Rong: "Identification of Third Order Volterra Kernels of Nonlinear Chemical Processes"Proc.AdCONIP held in Kumamoto, Japan. 411-416 (2002)

H.Kashiwagi、H.Harada、L.Rong：“非线性化学过程的三阶 Volterra 核的识别”Proc.AdCONIP 在日本熊本举行。

H.Kashiwagi, Y.Li: "Nonparametric Nonlinear Model Predictive Control"Korean J.Chem.Eng.. 21. 329-337 (2004)

H.Kashiwagi，Y.Li：“非参数非线性模型预测控制”韩国 J.Chem.Eng.. 21. 329-337 (2004)

M.Numata, H.Kashiwagi, H.Harada: "Extension of linear identification to nonlinear by use of Volterra kernel method"Proc. AdCONIP held in Kumamoto, Japan. 405-410 (2002)

M.Numata、H.Kashiwagi、H.Harada：“使用 Volterra 核方法将线性辨识扩展到非线性”Proc。