基于IGLS方法的MIMO二维ARMAX模型参数估计

Q4 Engineering

Control and Cybernetics Pub Date : 2021-09-01 DOI:10.2478/candc-2021-0020

Zohreh Hayati, M. Shafieirad, I. Zamani, Amir Hossein, A. Mehra, Zohreh Abbasi

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引用次数: 0

摘要

摘要本文提出了一种用于线性多输入多输出离散二维系统无偏辨识的迭代方法。本文讨论的系统具有具有外生输入的自回归移动平均模型（ARMAX模型）。该算法是在传统的迭代广义最小二乘法的基础上提出的。总之，本文提出了一种二维多输入多输出迭代广义最小二乘（2DMIGLS）算法来估计ARMAX模型的未知参数。最后，仿真结果表明，在存在有色噪声的情况下，该算法在估计模型未知参数方面具有高效性和准确性。

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

Abstract This paper presents an iterative method for the unbiased identification of linear Multiple-Input Multiple-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.

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来源期刊

Control and Cybernetics 工程技术-计算机：控制论

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： The field of interest covers general concepts, theories, methods and techniques associated with analysis, modelling, control and management in various systems (e.g. technological, economic, ecological, social). The journal is particularly interested in results in the following areas of research: Systems and control theory: general systems theory, optimal cotrol, optimization theory, data analysis, learning, artificial intelligence, modelling & identification, game theory, multicriteria optimisation, decision and negotiation methods, soft approaches: stochastic and fuzzy methods, computer science,