Algorithm of Robust Control for Multi-stand Rolling Mill Strip Based on Stochastic Multi-swarm Multi-agent Optimization

@InProceedings{10.1007/978-981-97-0975-5_22, author="Nikitina, Tatyana and Kuznetsov, Borys and Ruzhentsev, Nikolay and Havrylenko, Olena and Dergachov, Kostiantyn and Volosyuk, Valerii and Shmatko, Oleksandr and Popov, Anatoliy and Zhyla, Simeon and Pavlikov, Vladimir and Tserne, Eduard and Averyanova, Yuliya and Sushchenko, Olha and Zaliskyi, Maksym and Solomentsev, Oleksandr and Ostroumov, Ivan and Kuzmenko, Nataliia", editor="Shukla, Samiksha and Sayama, Hiroki and Kureethara, Joseph Varghese and Mishra, Durgesh Kumar", title="Algorithm of Robust Control for Multi-stand Rolling Mill Strip Based on Stochastic Multi-swarm Multi-agent Optimization", booktitle="Data Science and Security", year="2024", publisher="Springer Nature Singapore", address="Singapore", pages="247--255", abstract="A multi-stand rolling mill is a complex dynamic systems operation that requires accurate measurements of input material and precise automatic control of the formation process. In this paper, an algorithm of robust control by tension, thickness, and rolled streak loop on a multi-stand rolling mill based on a robust meta-model of the random processes of the longitudinal variation in rolled strip thickness is presented. Both problems of robust meta-model and robust control design reduced to zero-sum antagonistic vector games solutions calculated based on multi-swarm stochastic metaheuristic Archimedes optimization algorithm. The paper also presents a computer simulation of a designed robust system for a 3-stand 2-h tandem cold rolling mill. The utilization of the proposed algorithms gives the opportunity to decrease the change in strip tension and thickness in the inter-stand spaces of the rolling mill and decrease the system sensitivity in case of its parameter variation.", isbn="978-981-97-0975-5" }