Multi‐model predictive control of converter inlet temperature in the process of acid production with flue gas

Abstract

SummaryThe smelting of non‐ferrous metals produces substantial quantities of sulfur dioxide (SO)‐laden flue gas, which is seriously harmful to environment and humans. To improve the conversion ratio of SO and minimize environmental pollution, controlling converter inlet temperature during acid production has proven to be an efficient approach. However, unsteadiness of smelting procedure leads to frequent changes in the concentration of SO, which affects the catalytic conversion of SO and the production of sulfuric acid. To regulate converter inlet temperature, a proposed method of multi‐model predictive control is introduced. First, working conditions are divided and characterized according to the range of SO concentration. Then, the mathematical model is established for each working condition and the model predictive controller is designed. Finally, an effective switching mechanism is established to realize smooth switching under different working conditions and closed‐loop control of the whole system. Through simulation validation, compared with traditional single‐model predictive controllers and multi‐model PID controllers, the proposed approach demonstrates improved transient performance and steady‐state performance. Simulation outcomes clearly highlight the superiority of the proposed algorithm.