About this document
Neural Network Control in Steel Pickling by Jacky is a document available to read on EtoBox.
This document discusses using a neural network model predictive control (NNMPC) scheme for a multivariable nonlinear steel pickling process. The steel pickling process involves removing surface oxides from metal by immersing it in hydrochloric acid baths, which exhibit nonlinear dynamics and interactions between variables. Recurrent neural networks are used to model the multiple input, single output subsystem dynamics from simulation data. The neural network models are then used to predict states within the
- Author
- Jacky
- Language
- EN