Abstract: Waste incineration has become a key technology for the efficient treatment of domestic waste. To enhance incineration efficiency and reduce pollution, precise control of the combustion-supporting air in the incinerator has become a key research direction. The study proposed a combustion-supporting air control system for waste incinerators that integrated an automatic combustion control (ACC) system with artificial intelligence (AI). Through utilizing model predictive control (MPC) technology, the system achieved dynamic regulation of the combustion-supporting air, addressed the lag issues inherent in traditional proportional-integral-derivative (PID) control. MPC models are versatile and can directly handle the control of processes with pure lag. It has excellent tracking performance, strong disturbance resistance capability and high robustness. After the system acquired the evaporation volume and combustion parameters of the waste incinerator in real time, it used MPC model to predict the future frequency of the fans, and precisely regulated the air volume in each area through ACC to achieve efficient combustion control. Results showed that this system significantly improved the stability of the combustion process. After implementation, the discrete coefficients for main steam flow, boiler outlet oxygen content, and the temperature in the upper part of the burnout zone were reduced to 5.33%, 16.33%, and 6.10%, respectively, while the operational frequency of the air system equipment decreased by 87.06%.

Key words: predictive control, waste incinerator, auxiliary air, automatic combustion control, artificial intelligence