Multi-Network-Feedback-Error-Learning in pelletizing plant control

This work is devoted to present a control application in an industrial process of iron pellet cooking in an important mining company in Brazil. This work uses an adaptive control in order to improve the performance of the conventional controller already installed in the plant. The main strategy approached here is known Multi-Network-Feedback-Error-Learning (MNFEL), it uses multiple neural networks in the strategy Feedback-Error-Learning (FEL).

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