This paper derives practical dynamic models for the glass industrial manufacturing process to be then included in model-based control solutions. In particular, the first section of the plant, that is, the glass melting furnace is investigated: silica sand and recovered glass are used as raw materials, and through methane and oxygen combustion melt glass is obtained which is then sent to the condition and final processing sections. Routine input-output data are employed to identify models of the furnace, including the loading machine, the fan, and the gas burners. Models of the various control valves are also identified, and finally, the parameters for the existing PI/PID controllers are estimated. A decentralized scheme comprised of SISO controllers and a centralized architecture with a model predictive controller (MPC) are designed and compared in a simulation scenario. The MPC solution guarantees higher performance with respect to the decentralized scheme by reaching a good trade-off between velocity of response and reduced oscillations.

Model-based Control of a Glass Melting Furnace

Riccardo Bacci di Capaci
;
Leonardo Musi;Alberto Landi;Sami Barmada
2024-01-01

Abstract

This paper derives practical dynamic models for the glass industrial manufacturing process to be then included in model-based control solutions. In particular, the first section of the plant, that is, the glass melting furnace is investigated: silica sand and recovered glass are used as raw materials, and through methane and oxygen combustion melt glass is obtained which is then sent to the condition and final processing sections. Routine input-output data are employed to identify models of the furnace, including the loading machine, the fan, and the gas burners. Models of the various control valves are also identified, and finally, the parameters for the existing PI/PID controllers are estimated. A decentralized scheme comprised of SISO controllers and a centralized architecture with a model predictive controller (MPC) are designed and compared in a simulation scenario. The MPC solution guarantees higher performance with respect to the decentralized scheme by reaching a good trade-off between velocity of response and reduced oscillations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1257070
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