Original scientific paper

Adaptive neural event-triggered design for the molten steel level in a strip casting process

Y. J. Zhang ; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, China
L. B. Wu ; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, China

Abstract

This paper considers an adaptive neural event-triggered control problem of the molten steel level for twin roll strip casting systems with the inclined angle. Firstly, the model is improved and simplified into an affine nonlinear system by exploiting input compensation technique. Then, an adaptive observer is established based on radial basis function neural network (RBFNN). Furthermore, an adaptive event-triggered control scheme and corresponding adaptive updated laws are designed. It is proved that the proposed control method can guarantee the system output can follow reference signal and all closed-loop signals are bounded. Finally, the validity of the control scheme is verified through semi-experimental system dynamic model.

Keywords

casting process; strip; mathematic model; molten steel level control; radial basis function neural network (RBFNN)

Hrčak ID:

255990

URI

https://hrcak.srce.hr/255990

Publication date:

1.7.2021.

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