多变量方程误差类系统的部分耦合迭代辨识方法
|
摘要
针对多变量方程误差滑动平均系统,利用最小二乘原理和迭代搜索原理,给出了增广随机梯度辨识方法、递推增广最小二乘辨识方法、梯度迭代辨识方法和最小二乘迭代辨识方法.针对多变量方程误差滑动平均系统和多变量方程误差自回归滑动平均系统,将多变量系统分解为一些子系统,利用耦合辨识概念,讨论了梯度迭代辨识方法、部分耦合(子系统)梯度迭代辨识方法、子系统最小二乘迭代方法和部分耦合子系统最小二乘迭代辨识方法.进一步结合数据滤波技术,研究了多变量方程误差自回归滑动平均系统的子系统梯度迭代辨识方法、部分耦合(子系统)梯度迭代辨识方法、部分耦合子系统最小二乘迭代辨识方法.文中给出了几个典型算法的计算步骤.
For multivariable equation error moving average systems,this paper gives an extended stochastic gradient identification algorithm,a recursive extended least squares identification algorithm,a gradient based iterative(GI)identification algorithm and a least squares based iterative(LSI) identification algorithm,using the least squares principle and the iterative search principle. For multivariable equation error moving average systems and multivariable equation error autoregressive moving average systems,this paper uses the coupling identification concept and decomposes a multivariable system into several subsystems,derives the corresponding GI identification algorithm,partially coupled(subsystem) GI identification algorithm,subsystem LSI identification algorithm and partially coupled subsystem LSI identification algorithm. Furthermore,using the filtering technique,this paper studies the subsystem GI identification algorithm,partially coupled(subsystem) GI identification algorithm,partially coupled subsystem LSI identification algorithm for multivariable equation error autoregressive moving average systems. The computational steps for several typical identification algorithms are provided.
For multivariable equation error moving average systems,this paper gives an extended stochastic gradient identification algorithm,a recursive extended least squares identification algorithm,a gradient based iterative(GI)identification algorithm and a least squares based iterative(LSI) identification algorithm,using the least squares principle and the iterative search principle. For multivariable equation error moving average systems and multivariable equation error autoregressive moving average systems,this paper uses the coupling identification concept and decomposes a multivariable system into several subsystems,derives the corresponding GI identification algorithm,partially coupled(subsystem) GI identification algorithm,subsystem LSI identification algorithm and partially coupled subsystem LSI identification algorithm. Furthermore,using the filtering technique,this paper studies the subsystem GI identification algorithm,partially coupled(subsystem) GI identification algorithm,partially coupled subsystem LSI identification algorithm for multivariable equation error autoregressive moving average systems. The computational steps for several typical identification algorithms are provided.
引文
[1]丁锋.系统辨识新论[M].北京:科学出版社,2013DING Feng.System identification:New theory and methods[M].Beijing:Science Press,2013
[2]丁锋.系统辨识:辨识方法性能分析[M].北京:科学出版社,2014DING Feng.System identification:Performance analysis for identification methods[M].Beijing:Science Press,2014
[3]丁锋.系统辨识(1):辨识导引[J].南京信息工程大学学报:自然科学版,2011,3(1):1-22DING Feng.System identification.Part A:Introduction to the identification[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(1):1-22
[4]丁锋.系统辨识(2):系统描述的基本模型[J].南京信息工程大学学报:自然科学版,2011,3(2):97-117DING Feng.System identification.Part B:Basic models for system description[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(2):97-117
[5]丁锋.系统辨识(3):辨识精度与辨识基本问题[J].南京信息工程大学学报:自然科学版,2011,3(3):193-226DING Feng.System identification.Part C:Identification accuracy and basic problems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(3):193-226
[6]丁锋.系统辨识(4):辅助模型辨识思想与方法[J].南京信息工程大学学报:自然科学版,2011,3(4):289-318DING Feng.System identification.Part D:Auxiliary model identification idea and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(4):289-318
[7]丁锋.系统辨识(5):迭代搜索原理与辨识方法[J].南京信息工程大学学报:自然科学版,2011,3(6):481-510DING Feng.System identification.Part E:Iterative search principle and identification methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(6):481-510
[8]丁锋.系统辨识(6):多新息辨识理论与方法[J].南京信息工程大学学报:自然科学版,2012,4(1):1-28DING Feng.System identification.Part F:Multiinnovation identification theory and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(1):1-28
[9]丁锋.系统辨识(7):递阶辨识原理与方法[J].南京信息工程大学学报:自然科学版,2012,4(2):97-124DING Feng.System identification.Part G:Hierarchical identification principle and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(2):97-124
[10]丁锋.系统辨识(8):耦合辨识概念与方法[J].南京信息工程大学学报:自然科学版,2012,4(3):193-212DING Feng.System identification.Part H:Coupling identification concept and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(3):193-212
[11]丁锋.辨识方法的计算效率(1):递推算法[J].南京信息工程大学学报:自然科学版,2012,4(4):289-300DING Feng.Computational efficiency of the identification methods.Part A:Recursive algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(4):289-300
[12]丁锋.辨识方法的计算效率(2):迭代算法[J].南京信息工程大学学报:自然科学版,2012,4(5):385-401DING Feng.Computational efficiency of the identification methods.Part B:Iterative algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(5):385-401
[13]丁锋.辨识方法的计算效率(3):信息向量耦合算法[J].南京信息工程大学学报:自然科学版,2012,4(6):481-495DING Feng.Computational efficiency of the identification methods.Part C:Coupled information vector algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(6):481-495.
[14]丁锋,汪菲菲.多元系统耦合多新息随机梯度类辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(1):1-16DING Feng,WANG Feifei.Coupled multi-innovation stochastic gradient type identification methods for multivariate systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(1):1-16
[15]丁锋,汪菲菲,汪学海.多元伪线性回归系统部分耦合多新息随机梯度类辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(2):97-112DING Feng,WANG Feifei,WANG Xuehai.Partially coupled multi-innovation stochastic gradient type identification methods for multivariate pseudo-linear regressive systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(2):97-112
[16]丁锋,汪菲菲,汪学海.类多变量输出误差系统的耦合多新息辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(3):193-210DING Feng,WANG Feifei,WANG Xuehai.Coupled multi-innovation identification methods for multivariable output-error-like systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(3):193-210
[17]Ding F,Liu G,Liu X P.Partially coupled stochastic gradient identification methods for non-uniformly sampled systems[J].IEEE Transactions on Automatic Control,2010,55(8):1976-1981
[18]Ding F.Coupled-least-squares identification for multivariable systems[J].IET Control Theory and Applications,2013,7(1):68-79
[19]Wang D Q,Ding F,Zhu D Q.Data filtering based least squares algorithms for multivariable CARAR-like systems[J].International Journal of Control,Automation,and Systems,2013,11(4):711-717
[20]Wang D Q,Ding F,Chu Y Y.Data filtering based recursive least squares algorithm for Hammerstein systems using the key-term separation principle[J].Information Sciences,2013,222:203-212
[21]Ding F,Chen T.Hierarchical gradient-based identification of multivariable discrete-time systems[J].Automatica,2005,41(2):315-325
[22]Ding F,Chen T.Hierarchical least squares identification methods for multivariable systems[J].IEEE Transactions on Automatic Control,2005,50(3):397-402
[2]丁锋.系统辨识:辨识方法性能分析[M].北京:科学出版社,2014DING Feng.System identification:Performance analysis for identification methods[M].Beijing:Science Press,2014
[3]丁锋.系统辨识(1):辨识导引[J].南京信息工程大学学报:自然科学版,2011,3(1):1-22DING Feng.System identification.Part A:Introduction to the identification[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(1):1-22
[4]丁锋.系统辨识(2):系统描述的基本模型[J].南京信息工程大学学报:自然科学版,2011,3(2):97-117DING Feng.System identification.Part B:Basic models for system description[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(2):97-117
[5]丁锋.系统辨识(3):辨识精度与辨识基本问题[J].南京信息工程大学学报:自然科学版,2011,3(3):193-226DING Feng.System identification.Part C:Identification accuracy and basic problems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(3):193-226
[6]丁锋.系统辨识(4):辅助模型辨识思想与方法[J].南京信息工程大学学报:自然科学版,2011,3(4):289-318DING Feng.System identification.Part D:Auxiliary model identification idea and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(4):289-318
[7]丁锋.系统辨识(5):迭代搜索原理与辨识方法[J].南京信息工程大学学报:自然科学版,2011,3(6):481-510DING Feng.System identification.Part E:Iterative search principle and identification methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2011,3(6):481-510
[8]丁锋.系统辨识(6):多新息辨识理论与方法[J].南京信息工程大学学报:自然科学版,2012,4(1):1-28DING Feng.System identification.Part F:Multiinnovation identification theory and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(1):1-28
[9]丁锋.系统辨识(7):递阶辨识原理与方法[J].南京信息工程大学学报:自然科学版,2012,4(2):97-124DING Feng.System identification.Part G:Hierarchical identification principle and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(2):97-124
[10]丁锋.系统辨识(8):耦合辨识概念与方法[J].南京信息工程大学学报:自然科学版,2012,4(3):193-212DING Feng.System identification.Part H:Coupling identification concept and methods[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(3):193-212
[11]丁锋.辨识方法的计算效率(1):递推算法[J].南京信息工程大学学报:自然科学版,2012,4(4):289-300DING Feng.Computational efficiency of the identification methods.Part A:Recursive algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(4):289-300
[12]丁锋.辨识方法的计算效率(2):迭代算法[J].南京信息工程大学学报:自然科学版,2012,4(5):385-401DING Feng.Computational efficiency of the identification methods.Part B:Iterative algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(5):385-401
[13]丁锋.辨识方法的计算效率(3):信息向量耦合算法[J].南京信息工程大学学报:自然科学版,2012,4(6):481-495DING Feng.Computational efficiency of the identification methods.Part C:Coupled information vector algorithms[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2012,4(6):481-495.
[14]丁锋,汪菲菲.多元系统耦合多新息随机梯度类辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(1):1-16DING Feng,WANG Feifei.Coupled multi-innovation stochastic gradient type identification methods for multivariate systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(1):1-16
[15]丁锋,汪菲菲,汪学海.多元伪线性回归系统部分耦合多新息随机梯度类辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(2):97-112DING Feng,WANG Feifei,WANG Xuehai.Partially coupled multi-innovation stochastic gradient type identification methods for multivariate pseudo-linear regressive systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(2):97-112
[16]丁锋,汪菲菲,汪学海.类多变量输出误差系统的耦合多新息辨识方法[J].南京信息工程大学学报:自然科学版,2014,6(3):193-210DING Feng,WANG Feifei,WANG Xuehai.Coupled multi-innovation identification methods for multivariable output-error-like systems[J].Journal of Nanjing University of Information Science and Technology:Natural Science Edition,2014,6(3):193-210
[17]Ding F,Liu G,Liu X P.Partially coupled stochastic gradient identification methods for non-uniformly sampled systems[J].IEEE Transactions on Automatic Control,2010,55(8):1976-1981
[18]Ding F.Coupled-least-squares identification for multivariable systems[J].IET Control Theory and Applications,2013,7(1):68-79
[19]Wang D Q,Ding F,Zhu D Q.Data filtering based least squares algorithms for multivariable CARAR-like systems[J].International Journal of Control,Automation,and Systems,2013,11(4):711-717
[20]Wang D Q,Ding F,Chu Y Y.Data filtering based recursive least squares algorithm for Hammerstein systems using the key-term separation principle[J].Information Sciences,2013,222:203-212
[21]Ding F,Chen T.Hierarchical gradient-based identification of multivariable discrete-time systems[J].Automatica,2005,41(2):315-325
[22]Ding F,Chen T.Hierarchical least squares identification methods for multivariable systems[J].IEEE Transactions on Automatic Control,2005,50(3):397-402