Semantic Scholar Open Access 2020 66 sitasi

Neural Network-Based Model Predictive Control of a Paste Thickener Over an Industrial Internet Platform

F. Núñez Saúl Langarica Pablo Diaz M. Torres Juan Carlos Salas

Abstrak

This article presents a real implementation of a neural network-based model predictive control scheme (NNMPC) to control an industrial paste thickener. The implementation is done over an Industrial Internet of Things (IIoT) platform designed using the seven layer reference model for IIoT systems. Modeling is achieved using an encoder–decoder with attention recurrent neural network, while MPC search is done using particle swarm optimization. An industrial evaluation is presented, which highlights the set-point tracking and disturbance rejection capabilities of the proposed NNMPC technique.

Topik & Kata Kunci

Computer Science

Penulis (5)

F. Núñez

Saúl Langarica

Pablo Diaz

M. Torres

Juan Carlos Salas

Format Sitasi

APA MLA BibTeX

Núñez, F., Langarica, S., Diaz, P., Torres, M., Salas, J.C. (2020). Neural Network-Based Model Predictive Control of a Paste Thickener Over an Industrial Internet Platform. https://doi.org/10.1109/TII.2019.2953275

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 66×
Sumber Database: Semantic Scholar
DOI: 10.1109/TII.2019.2953275
Akses: Open Access ✓