|Development of Predictive Model based Control Scheme for a Molten Carbonate Fuel Cell (MCFC) Process
Tae Young Kim, Beom Seok Kim, Tae Chang Park, and Yeong Koo Yeo*
International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp.791-803, 2018
Abstract : "To improve availability and performance of fuel cells, the operating temperature of a molten carbonate
fuel cells (MCFC) stack should be strictly maintained within a specified operation range and an efficient control
technique should be employed to meet this objective. While most of modern control strategies are based on process
models, many existing models for a MCFC process are not ready to be applied in synthesis and operation of control
systems. In this study, auto-regressive moving average (ARMA) model, least square support vector machine (LSSVM)
model and artificial neural network (ANN) model for the MCFC system are developed based on input-output
operating data. Among these models, the ARMA model showed the best tracking performance. A model predictive
control (MPC) method for the operation of a MCFC process is developed based on the proposed ARMA model.
For the purpose of comparison, a MPC scheme based on the linearized rigorous model for a MCFC process is
developed. Results of numerical simulations show that MPC based on the ARMA model exhibits better control
performance than that based on the linearized rigorous model."
ARMA modeling, model predictive control, molten carbonate fuel cells, rigorous model.
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