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Recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method

A technique of least squares and model identification, applied to instruments, adaptive control, control/regulation systems, etc., can solve the problem that ARMAX models cannot achieve parameter estimation

Active Publication Date: 2012-07-04
QIDONG XIANFENG HIGH PRESSURE PUMP CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the traditional least squares method can only be used for ARX model identification, parameter estimation cannot be realized for the ARMAX model with colored noise interference, so it is necessary to use the augmented least squares method to identify the crystallizer ARMAX model to obtain the Model parameters

Method used

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  • Recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method
  • Recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method
  • Recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method

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Experimental program
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Embodiment 1

[0056] Table 1 shows the sampling data of a slab continuous casting machine crystallizer in a steel plant, the sampling time interval Ts = 0.003 seconds, and the number of data points N = 250.

[0057] Select the ARMAX crystallizer model of na=5, nb=3, nc=2;

[0058] Let A(q)=1+a 1 q -1 +a 2 q -2 +a 3 q -3 +a 4 q -4 +a 5 q -5 , B(q)=b 1 q -1 +b 2 q -2 +b 3 q -3 , then the system parameters to be identified are θ ^ 0 = a 1 a 2 a 3 a 4 a 5 b ...

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Abstract

The invention relates to a recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method, which specifically comprises the following steps of: by taking crystallizer oil cylinder valve opening as input u and crystallizer position as output y, establishing least square and an indicator function of a crystallizer ARMAX model based on sampled data; computing a residual error e as a white noise estimated value by using model parameters obtained by previous computation; constituting variables u, y and e into a vector; and gradually computing variables Pk and Lk according to the idea of the recursive least squares algorithm, and gradually performing iterative computation through Pk and Lk to obtain unknown parameters of the model. According to the method, a globally optimal solution of the unknown parameters of the crystallizer ARMAX model can be accurately approximated, and the parameters of the crystallizer ARMAX model can be updated by using current sampled input and output data; the updating of the parameters of the crystallizer ARMAX model does not depend on historical data; and accurate ARMAX model identification parameters can be timely provided when the model parameters change.

Description

technical field [0001] The present invention relates to the field of mold control system design for continuous casting machines in the iron and steel metallurgy industry, in particular to a mold ARMAX (Auto Regressive Moving Average eXogenous) model based on Recursive Extended Least Squares Algorithm (RELS) identification method. Background technique [0002] Mold vibration has a direct and important impact on the stripping and surface quality of the slab. In the actual casting process of slab continuous casting, the casting speed usually changes with the change of working conditions (such as casting temperature). To ensure a good stripping effect and surface quality of the slab, the basic vibration parameters such as frequency and amplitude should be adjusted appropriately on the premise of ensuring that the vibration process parameters are basically stable. However, in order to obtain a good frequency and amplitude control effect, a reasonable crystallizer control system ...

Claims

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Application Information

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IPC IPC(8): G05B13/04B22D11/057
Inventor 张华军蔡炜褚学征陈方元尉强周登科
Owner QIDONG XIANFENG HIGH PRESSURE PUMP CO LTD