Abstract: The increasing annual production of industrial solid waste has imposed significant pressure on pollution control. Incineration has emerged as a mainstream treatment method due to its comprehensive advantages. However, traditional incineration control primarily relies on manual operation, leading to issues such as delayed regulation, low efficiency, and unstable pollutant emissions. Consequently, intelligent optimization control for industrial solid waste incineration has become a key research focus in the industry. A circulating fluidized bed (CFB) incinerator in Zhejiang province was taken as the research object. To address its low automation level and insufficient intelligent control, an intelligent optimization control system was developed and implemented. The system collects real-time operational data through a distributed control system (DCS) and constructs an accurate combustion state recognition model. By integrating multiple optimization algorithms and control strategies, it achieves real-time regulation of key operational parameters. Through comparative analysis of operational data before and after system implementation, the results demonstrated that the system could enable precise control of critical variables such as air distribution and steam-water balance. Moreover, it significantly improved operational stability, safety, and pollutant emission control effect. Key performance indicators, including main steam temperature deviation, drum water level fluctuation, and excess range of CO emission concentration, showed notable reductions. The successful application of this intelligent control system not only enhances incinerator efficiency and environmental performance, but also provides robust technical support for the intelligent development of the solid waste incineration industry, thereby promoting the improvement of the automation and intelligent operation level of incineration processes.

Key words: industrial solid waste incineration, intelligent control, system development, control performance