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Research on Automatic Gauge Control Based on Smith Adaptive Identification

Author: ZhangShuo
Tutor: LiuJianChang
School: Northeastern University
Course: Control Theory and Control Engineering
Keywords: automatic gauge control smith predictor model reference adaptive identification
CLC: TP273
Type: Master's thesis
Year: 2010
Downloads: 37
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Abstract


The thickness accuracy is one of the most important quality indexes for cold strip rolling production and automatic gauge control is the key technology to improve the quality of strip. With the continuous development of the scientific and technology, the production and the quality of the plate and strip rolling mill is increasingly becoming the primary objective of the pursuit. So it is is essential to study in-depth in mill thickness control.Based on the characterstic of time-delay exists and changing of parameters in Thickness gauge feedback AGC system, it uses the compensation function of Smith predictor to constitute the system of Smith-AGC in actual production line. As follow are the concrete research contents:(1) Factors that affect system performance are analyed and these factors are interference and accuracy of estimated model.(2) This thesis gives a structure modified Smith predictor to enhance the capacity of resisting disturbance and verifies performance of this system by mathematical derivation and simulation.(3) In order to make predictor parameters accurate, it uses laser velometer to measure the time delay of AGC system and uses identifier based on model reference adaptive Identification algorithm to identify the plant parameters and then modifies the model to the non-time-delay part of the Smith predictor. So the object model parameters and predictor parameters can maintain congruously to overcome the influence on model parameters matching accuracy when parameters chang in rolling process.This thesis makes some simulation about the automatic gauge control system base on model reference adaptive identified Smith predictor. Smulation results show that the identification algorithm can adjust model parameters within30cycles when there is model mismatching and this system still has good control performance to enhance the thickness accuracy when there are disturbances.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Automatic control,automatic control system
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