Abstract
Microstructure and mechanical properties of hot-rolled strips are directly influenced by coiling temperature, and feedback control is one of the most significant approaches to improve coiling temperature control precision. Laminar cooling control system was introduced, and the novel feedback control algorithm based on proportional–integral controller and Smith predictor was designed, respectively, and the online adaptive algorithm was used to optimize parameters of proportional–integral controller. This control system has been successfully applied in a hot strip mill, and the record curves indicate that the novel feedback control system can get better dynamic characteristic. The coiling temperature can be precisely controlled with a high accuracy of ±15°C over 98.3%.
Highlights
As an important elementary industry of national economy, the iron and steel enterprises are facing serious resource and energy shortages with the rapid development of society and the increasing environmental pressure
Considering the response speed and the steady-state precision, the novel feedback control system based on PI controller was designed with Smith predictor, the method of variable segment length was used, and the optimal control strategy based on the variable segment length method was derived
After a long time of debugging, the novel feedback control system has been applied to the production of various specifications, comparing with the traditional feedback control system based on typical second-order optimality and Smith predictor, the novel feedback control system has faster response speed and higher steady-state precision
Summary
As an important elementary industry of national economy, the iron and steel enterprises are facing serious resource and energy shortages with the rapid development of society and the increasing environmental pressure. Keywords Hot strip mill, coiling temperature, feedback control, Smith predictor, online adaptive algorithm Liu et al.[8] designed integration controller based on Smith predictor to improve the coiling temperature control precision.
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