Model predictive control of semiautogenous mills (sag)-Reference-Cited by-同舟云学术

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Model predictive control of semiautogenous mills (sag)

Published:2014-10 Issue: Volume:64 Page:92-96
ISSN:0892-6875
Container-title:Minerals Engineering
language:en
Short-container-title:Minerals Engineering

Author:

Salazar José-Luis,Valdés-González Héctor,Vyhmesiter Eduardo,Cubillos Francisco

Publisher

Elsevier BV

Subject

Mechanical Engineering,Geotechnical Engineering and Engineering Geology,General Chemistry,Control and Systems Engineering

Reference25 articles.

1. Inferential measurement of SAG mill parameters II: state estimation;Apelt;Miner. Eng.,2002

2. Inferential measurement of SAG mill parameters III: inferential models;Apelt;Miner. Eng.,2002

3. A mill power equation for SAG mills;Austin;Miner. Metall. Process.,1990

4. Advanced control of gold ore grinding plants in South Africa;Bouche;Miner. Eng.,2005

5. Application of model predictive control in ball mill grinding circuit;Chen;Miner. Eng.,2007

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1. Multivariable predictive models for the estimation of power consumption (kW) of a Semi-autogenous mill applying Machine Learning algorithms [Modelos predictivos multivariables para la estimación de consumo de potencia (kW) de un molino Semi - autógeno aplicando algoritmos de Machine Learning];Journal of Energy & Environmental Sciences;2024-03-10

2. Using Discrete Element Method to Analyse the Drop Ball Test;Minerals;2024-02-21

3. Machine Learning Algorithms for Semi-Autogenous Grinding Mill Operational Regions’ Identification;Minerals;2023-10-25

4. Effective Throughput Optimization of SAG Milling Process Based on BPNN and Genetic Algorithm;2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS);2023-05-08

5. Multiobjective Tuning Technique for MPC in Grinding Circuits;IEEE Access;2023

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