Data-driven control for combustion process of circulating fluidised bed boiler

Owing to the advantages of burning low-quality coal (coal slime and coal gangue), furnace desulfurisation, low NOx emission and deep load adjustment, the circulating fluidised bed (CFB) combustion technology becomes one of the few fossil fuel utilisation technologies funded continuously by the Chinese government. However, compared with the pulverised coal boiler, the combustion process of CFB boiler is more complicated because of the larger time delay, significant uncertainty and more coupled variables. In this study, a data-driven proportional-integral-derivative (DD-PID) control strategy is presented for the combustion control of CFB boiler to improve the operating performance under full operating conditions. By analysing the running mechanism of combustion process, an inverse decoupler is introduced to transfer the combustion object to the generalised controlled object, which has relatively independent input-output relationship. After that, a normative procedure of DD-PID, including PID-parameter database establishment, information-vector neighbourhood selection, active PID-parameter determination, database update, and redundant vector deletion, is given. Finally, a series of case study, including numerical tests applied to the proposed combustion model and application test employed on 330MW CFB simulation platform proves the feasibility of DD-PID control strategy.