Title

MODEL BASED OPTIMIZING CONTROL SYSTEM IMPLEMENTED FOR THE CONTROL OF THE PELLETIZING FURNACES AT CIA. VALE DO RIO DOCE – VITÓRIA – ES - BRAZIL

MODEL BASED OPTIMIZING CONTROL SYSTEM IMPLEMENTED FOR THE CONTROL OF THE PELLETIZING FURNACES AT CIA. VALE DO RIO DOCE – VITÓRIA – ES - BRAZIL

Authorship

MARTINS, MARCO AURÉLIO SOARES; SILVA, CACIO JOSE DA; RIBEIRO, MAGNO RODRIGUES; LOPES, EVENILSON SOPRANI; FERRI, LEONARDO NOGUEIRA; FILHO, JOSE XAVIER DA SILVA; DALVI, SERGIO LUIS; STELZER, ALEXANDRE CABRAL; MENDES, MARCELO CIMINELLI; BOUCHÉ, CHRISTOPHE

MARTINS, MARCO AURÉLIO SOARES

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SILVA, CACIO JOSE DA

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RIBEIRO, MAGNO RODRIGUES

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LOPES, EVENILSON SOPRANI

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FERRI, LEONARDO NOGUEIRA

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FILHO, JOSE XAVIER DA SILVA

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DALVI, SERGIO LUIS

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STELZER, ALEXANDRE CABRAL

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MENDES, MARCELO CIMINELLI

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BOUCHÉ, CHRISTOPHE

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DOI

10.5151/2594-357x-34Red-983-992

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Abstract

The automation process in the mineral industry is an area where the control strategies are quickly incorporating the technological evolution of advanced control techniques. This is due to difficulties in controlling highly interdependent loops, with big delay times which are hard to observe, at the same time that several process parameters can not be measured on line. Some aspects and deficiencies about conventional control technologies are discussed and the advanced optimizing process control techniques which apply artificial intelligence like: expert systems, physical process models, neural networks and fuzzy logic are shown. The advantages of using the Model-Based Optimizing Control for the mineral industry providing significant performance gains, when compared to conventional technologies are emphasized.

The automation process in the mineral industry is an area where the control strategies are quickly incorporating the technological evolution of advanced control techniques. This is due to difficulties in controlling highly interdependent loops, with big delay times which are hard to observe, at the same time that several process parameters can not be measured on line. Some aspects and deficiencies about conventional control technologies are discussed and the advanced optimizing process control techniques which apply artificial intelligence like: expert systems, physical process models, neural networks and fuzzy logic are shown. The advantages of using the Model-Based Optimizing Control for the mineral industry providing significant performance gains, when compared to conventional technologies are emphasized.

Keywords

Optimizing Control, Mathematical Model, OCS and Fuzzy Logic Control

Optimizing Control, Mathematical Model, OCS and Fuzzy Logic Control