Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling [version 2; peer review: 2 approved] - Shang Chen; Jie Sun; Wen Peng; Cheng-yan Ding; Dian-hua Zhang (Digital Twin)
During the hot rolling process, the performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension control method remain restricted by a lack of intelligent parameter maintenance strategies. To address this challenge and enhance the smart manufacturing capabilities of strip hot rolling, based on the digital twin method, this paper proposes a data-driven optimized control method for the gauge-looper-tension system of strip hot rolling. First, a hot rolling process model is constructed based on a digital twin method to serve as an evaluation and optimization platform. Subsequently, relevant data are collected to calculate the Hurst index for identifying the performance of the controller during the rolling process. Additionally, for controllers with poor Hurst index values, the crayfish optimization algorithm is employed for adjusting controller parameters to maximize the Hurst index. Experimental results demonstrate that the evaluation method effectively recognized the control state of gauge-looper-tension system and the optimization method successfully enhances the performance of the control system. Therefore, based on the digital twin platform, the proposed method can effectively maintain performance-degraded control systems.