Parameter estimation of MIMO two-dimensional ARMAX model based on IGLS method

• Autorzy: Hayati Zohreh , Shafieirad Mohsen , Zamani Iman , Amiri Mehra Amir Hossein , Abbasi Zohreh
• Języki publikacji: EN

Abstrakty

EN

This paper presents an iterative method for the unbiased identification of linearMultiple-InputMultiple-Output (MIMO) discrete two-dimensional (2D) systems. The system discussed here has Auto-Regressive Moving-Average model with exogenous inputs (ARMAX model). The proposed algorithm functions on the basis of the traditional Iterative Generalized Least Squares (IGLS) method. In summary, this paper proposes a two-dimensional Multiple-Input Multiple-Output Iterative Generalized Least Squares (2DMIGLS) algorithm to estimate the unknown parameters of the ARMAX model. Finally, simulation results show the efficiency and accuracy of the presented algorithm in estimating the unknown parameters of the model in the presence of colored noise.

Słowa kluczowe

EN

ARMAX model; discrete 2D systems; iterative identification; MIMO system; parameter estimation

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2021
• Tom: Vol. 50, No. 3
• Strony: 303--322
• Opis fizyczny: Bibliogr. 21 poz., rys., tab.

Twórcy

autor

Hayati Zohreh

• Faculty of Electrical Engineering, Allameh Feyz Kashani Institute of Higher Education, Kashan, Iran

autor

Shafieirad Mohsen

• Department of Electrical and Computer Engineering, University of Kashan, Kashan, Iran

autor

Zamani Iman

• Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran

autor

Amiri Mehra Amir Hossein

• Department of Electrical and Computer Engineering, University of Kashan, Kashan, Iran

autor

Abbasi Zohreh

• Department of Electrical and Computer Engineering, University of Kashan, Kashan, Iran

Bibliografia

• Abbasi, Z., Zamani, I., Amiri Mehra, A. H. and Shafieirad, M. (2020) Optimal Control Design of Impulsive SQEIAR Epidemic Models with Application to COVID-19. Chaos, Solitons & Fractals, 139, 110054.
• Ali, M., Chughtai, S. S. and Werner, H. (2010) Consistent identification of two-dimensional systems. In: American Control Conference (ACC), June 2010, 3464-3469, IEEE.
• Amiri Mehra, A. H., Shafieirad, M., Abbasi, Z. and Zamani, I. (2020) Parameter Estimation and Prediction of COVID-19 Epidemic Turning Point and Ending Time of a Case Study on SIR/SQAIR Epidemic Models. Journal of Computational and Mathematical Methods in Medicine, December 29th, 2020. https://doi.org/10.1155/2020/1465923
• Bracewell, R. N. (1995) Two-Dimensional Imaging. Prentice Hall, Englewood Cliffs.
• Chen, C. T. and Kao, Y. S. (1979) Identification of two-dimensional transfer functions from finite input-output data. IEEE Transactions on Automatic Control, 24(5), 748-752.
• Ding, D. W., Du, X. and Li, X. (2015) Finite-frequency model reduction of two-dimensional digital filters. IEEE Transactions on Automatic Control, 60(6), 1624-1629.
• Fornasini, E. and Marchesini, G. (1978) Doubly-indexed dynamical systems: State-space models and structural properties. Mathematical Systems Theory, 12(1), 59-72.
• Fraanje, R. and Verhaegen, M. (2005) A spatial canonical approach to multidimensional state-space identification for distributed parameter systems. In: Multidimensional Systems, July 2005. NDS 2005. The Fourth International Workshop on. IEEE, 217-222.
• Frank, P. M. (1999) Advances in Control. Springer.
• Garnier, H. and Wang, L. (2008) Identification of Continuous-time Models from Sampled Data. Springer.
• Kaczorek, T. (1985) Two-Dimensional Linear Systems. Springer.
• Marszalek, W. (1984) Two-dimensional state-space discrete models for hyperbolic partial differential equations. Applied Mathematical Modelling, 8 (1), 11-14.
• Norton, J.P. (1986) An Introduction to Identification. Academic Press.
• Sadeghi, M., Shafiee, M. and Shafieirad, M. (2013) A new approach to improve defect detection of steel sheets using Gabor wavelet. International Journal of Information and Electronics Engineering, 3(5), 541.
• Shafieirad, M. and Shafiee, M. (2008) A mobility-aware cross-layer congestion control, routing and scheduling design in ad-hoc wireless networks. In: 11 th International Conference on Optimization of Electrical and Electronic Equipment. May 2008, IEEE, 191-200.
• Shafieirad, M., Shafiee, M. and Abedi, M. (2013) Identification of linear partial difference equations with constant coefficients. J. Basic Appl. Sci. Res., 3(1), 655-660.
• Shafieirad, M., Shafiee, M. and Abedi, M. (2014a) Estimation of Space and Time Shifts in Continuous 2-D Systems Using Instrumental Variable. Canadian Journal of Electrical and Computer Engineering, 37(1), 42-47.
• Shafieirad, M., Shafiee, M. and Abedi, M. (2014b) Recursive identification of continuous two-dimensional systems in the presence of additive colored noise. IETE Journal of Research, 60(1), 74-84.
• Wang, Y., Zhao, D., Li, Y. and Ding, S. X. (2017) Unbiased minimum variance fault and state estimation for linear discrete time-varying two-dimensional systems. IEEE Trans. Autom. Control, 62(10), 5463-5469.
• Zeinali, M. and Shafiee, M. (2016) A new Levinson–Durbin based 2-D AR model parameter estimation method. Multidimensional Systems and Signal Processing, 27(2), 341-357.
• Zhao, D., Wang, Y., Li, Y. and Ding, S. X. (2017) H∞ fault estimation for 2-D linear discrete time-varying systems based on Krein space method. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(12), 2070-2079.