Online self-optimizing control of coal-fired boiler combustion system

Coal-fired boiler combustion system is a complex multiinput and multioutput plant with strong nonlinear and large time-delay. What´s more, it is difficult to establish accurate mathematical model. Because the oxygen content signal has large time-delay and air leak exists, traditional combustion control method that uses oxygen meter to decide air flow is inefficient. Aiming at common problems in the boiler combustion process and based on heat balance principle, this paper adopts the variable oxygen content correction project which sets optimal excess air ratio according to current combustion thermal efficiency and dynamic self-optimizing control which can self-search optimal combustion state. The air/fuel ratio can be adjusted on-line to maintain the optimal combustion condition. Local experiment proves that adopting dynamic self-optimizing control to search optimal air/fuel ratio in combustion process can improve boiler´s thermal efficiency and achieve the goal of optimal combustion.