Nash equilibrium-based distributed predictive control strategy for thickness and tension control on tandem cold rolling system

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. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

A distributed model predictive control (DMPC) strategy based on the Nash equilibrium is proposed in this study to improve the strip accuracy and product stability of the tandem cold rolling process. Its performance and effectiveness are demonstrated through a series of experiments based on rolling data from industry.