Resumo

MONTERO GONGORA, Deynier et al. NARX model of post-combustion in a lateritic ore reduction furnace. EAC [online]. 2022, vol.43, n.3, pp. 15-28.  Epub 14-Fev-2023. ISSN 1815-5928.

The Nickel and Cobalt Production Company "Comandante Ernesto Che Guevara" plays an essential role in the economic development of Cuba. Within the industrial production process, the lateritic ore reduction furnace is a key stage and requires a high consumption of fuel oil, which represents around 40% of the unit cost per ton produced of nickel plus cobalt, making it vital. reduce such costs. The implementation of the automatic control system in post-combustion has been affected by not having mathematical models of this process. In the present investigation, a black box model based on artificial neural networks that reflects the dynamic characteristics of the process is proposed. The methodology used consists of carrying out passive experiments of 10-months operating time period for the preparation of a recurrent algorithm that includes the methods of random cross validation and the Akaike’s information criterion. As a result, a NARX model (non-linear autoregressive structure with external inputs) was obtained that predicts the temperatures of hearths four and six, obtaining a mean square error of less than 5 °C, with a prediction horizon one step ahead (120s). The accuracy achieved with the model contributes to predicting the thermal profile in the heating zone of the furnace, as a basis for the design of control strategies that guarantee a better use of energy and of the reducing additive fuel, which would reduce process losses. and environmental pollution.

Palavras-chave : reduction furnace; post-combustion; NARX model; random cross-validation; Akaike´s information criteria.

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