基于SCR的烟气脱硝系统优化研究

Research on optimization of flue gas denitrification system based on SCR

针对传统串级控制SCR脱硝系统存在调节时间较长、抗干扰性差等问题。采用前馈预估理论,引入Smith预估补偿装置,消除模型滞后产生的不利影响。结合模糊控制,利用其参数自整定性能,提高模型适应能力。经Simulink仿真表明:模糊PID-Smith预估控制,能够有效减少调节时间,将超调量和稳态误差降到最低。最后将该控制方法应用到S7-300系列PLC中实现,实践证明该方法稳定可靠,适用于工业脱硝系统。

The traditional cascade control SCR denitration system has problems such as long adjustment time and poor anti-interference.The feedforward prediction theory is adopted and the Smith prediction compensation device is introduced to eliminate the adverse effects of model lag.Combined with fuzzy control,use its parameter self-tuning performance to improve model adaptability.Simulink simulation shows that the fuzzy PID-Smith predictive control can effectively reduce the adjustment time and minimize the overshoot and steadystate error.Finally,the control method is applied to the S7-300 series PLC to realize it.Practice has proved that the method is stable and reliable,and it is suitable for industrial denitration system.