Least Squares based Iterative Parameter Estimation Algorithm for Stochastic Dynamical Systems with ARMA Noise Using the Model Equivalence
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By means of the model equivalence theory, this paper proposes a model equivalence based least squares iterative algorithm for estimating the parameters of stochastic dynamical systems with ARMA noise. The proposed algorithm reduces the number of the unknown noise terms in the information vector and can give more accurate parameter estimates compared with the generalized extended least squares algorithm. The validity of the proposed method is evaluated through a numerical example.
KeywordsDynamical system iterative method least squares model equivalence parameter estimation
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- Y. Wei, J. Qiu, H. R. Karimi, and M. Wang, “New results on H-infinity dynamic output feedback control for Markovian jump systems with time-varying delay and defective mode information,” Optimal Control, Applications and Methods, vol. 35, no. 6, pp. 656–675, November 2014. [click]MathSciNetCrossRefMATHGoogle Scholar
- F. Ding, F. F. Wang, L. Xu, and M. H. Wu, “Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering,” Journal of the Franklin Institute, vol. 354, no. 3, pp. 1321–1339, February 2017. [click]MathSciNetCrossRefMATHGoogle Scholar
- T. Söderström, M. Hong, J. Schoukens, and R. Pintelon, “Accuracy analysis of time domain maximum likelihood method and sample maximum likelihood method for errors-in-variables and output error identification,” Automatica, vol. 46, no. 4, pp. 721–727, April 2010. [click]MathSciNetCrossRefMATHGoogle Scholar
- J. H. Li, W. X. Zheng, J. P. Gu, and L. Hua, “Parameter estimation algorithms for Hammerstein output error systems using Levenberg-Marquardt optimization method with varying interval measurements,” Journal of the Franklin Institute, vol. 354, no. 1, pp. 316–331, January 2017.MathSciNetCrossRefMATHGoogle Scholar
- D. D. Meng and F. Ding, “Identification of stochastic systems with colored noise by the model equivalence theory,” The 28th Chinese Control and Decision Conference, Yinchuan, China, pp. 5842–5847, May 2016.Google Scholar
- F. Ding, Y. J. Wang, J. Y. Dai, Q. S. Li, and Q. J. Chen, “A recursive least squares parameter estimation algorithm for output nonlinear autoregressive systems using the inputoutput data filtering,” Journal of the Franklin Institute, vol. 354, no. 15, pp. 6938–6955, October 2017.MathSciNetCrossRefMATHGoogle Scholar
- L. Xu, “The parameter estimation algorithms based on the dynamical response measurement data,” Advances in Mechanical Engineering, vol. 9, no. 11, pp. 1–12, November 2017. [click]Google Scholar
- J. L. Ding, “Recursive and iterative least squares parameter estimation algorithms for multiple-input-output-error systems with autoregressive noise,” Circuits, Systems and Signal Processing, vol. 37, 2018. doi: 10.1007/s00034-017-0636-0 [click]Google Scholar
- J. L. Ding, “The hierarchical iterative identification algorithm for multi-input-output-error systems with autoregressive noise,” Complexity, 2017, 1–11. Article ID5292894. https://doi.org/10.1155/2017/5292894Google Scholar