Nash equilibrium-based distributed predictive control strategy for thickness and tension control on tandem cold rolling system. (January 2021)

• Record Type: Journal Article
• Authors: Hu, Yunjian; Sun, Jie; Peng, Wen; Zhang, Dianhua
• Is Part Of: Journal of process control. Volume 97(2021)
• Page Start: 92
• Page End: 102
• Publication Date: 2021-01
• Subjects: Tandem cold rolling -- Thickness control -- Tension control -- Nash equilibrium -- Distributed model predictive control; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2020.11.014
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: With the increasing demands on strip product quality, conventional control methods cannot break the cold rolling production bottleneck The development of advanced control algorithms provides theoretical support for the improvement of strip accuracy and product stability of the tandem cold rolling process. Considering the complex characteristics of the system, a distributed model predictive control (DMPC) strategy based on the Nash equilibrium is proposed in this study. A state space model including the rolling process with constraints is established. To improve the calculation speed, a Laguerre function is integrated in the control strategy, so as to reduce the parameter dimension. The DMPC online optimal control strategy based on the Nash equilibrium is proposed to solve the problem between the constrained multivariable complex system and online rolling optimization. Its performance and effectiveness are demonstrated through a series of experiments based on rolling data from industry. Highlights: A state space model of thickness and tension during rolling process is established. A DMPC strategy based on Nash Equilibrium is designed for the rolling system. The DMPC strategy of the whole rolling system shows excellent control performance.