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A maximum likelihood-recursive least square identification algorithm of a multi-variable difference equation model

A technique of recursive least squares and difference equations, applied in complex mathematical operations, etc., and can solve problems such as complex modeling and identification of multivariable systems, high dimensions, and many variables in multivariable systems.

Inactive Publication Date: 2016-08-17
NANTONG UNIVERSITY
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Problems solved by technology

Compared with the univariate system, the modeling and identification of the multivariate system are more complicated than the univariate system due to the large number of variables, high dimensionality and complex structure.

Method used

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  • A maximum likelihood-recursive least square identification algorithm of a multi-variable difference equation model
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  • A maximum likelihood-recursive least square identification algorithm of a multi-variable difference equation model

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Embodiment Construction

[0066] A maximum likelihood recursive least squares identification algorithm for a multivariate differential equation model, comprising the following steps:

[0067] (1) According to the existing maximum likelihood principle, a sub-system maximum likelihood criterion function in the multivariable difference equation model is constructed:

[0068] J ( θ i , t ) = 1 2 Σ k = 1 t v i 2 ( k )

[0069] Explanation of the symbols in the above formula: θ i As the parameter vector of the recursion time t, as an information vector;

[0070] (2) Based on the maximum likelihood criterion function of the subsystem in the multivariate diff...

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Abstract

The invention discloses a maximum likelihood recursive least squares identification algorithm for a multivariable difference equation model, including constructing a subsystem maximum likelihood in a multivariate difference equation model based on the existing maximum likelihood principle Criterion function; based on the maximum likelihood criterion function of the subsystem in the multivariate difference equation model, the implementation process of the maximum likelihood recursive least squares identification algorithm for the multivariate difference equation model is constructed; a set of multivariate difference equations is constructed Model maximum likelihood recursive least squares identification algorithm. The invention adopts the principle of maximum likelihood and a recursive identification method, and is applied to parameter estimation of a linear multivariable system.

Description

technical field [0001] The invention relates to a maximum likelihood recursive least square identification algorithm for a multivariate difference equation model. Background technique [0002] Mathematical models play a very important role in the field of control and other engineering fields. They are used to describe the relationship between system variables. Practical systems in many industries can be modeled as multivariable systems, which are characterized by multiple input and output variables in the system. Compared with the univariate system, the modeling and identification of the multivariate system are more complicated than the univariate system because of the large number of variables, high dimensionality and complex structure. Multivariable systems can be described by different mathematical models, such as state-space models, transfer function models, and so on. The invention is suitable for parameter identification of multi-variable difference equation models. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/17
CPCG06F17/17
Inventor 李俊红杨奕朱建红李晨杨赛张晴李建国
Owner NANTONG UNIVERSITY
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