Dynamically decoupling control algorithm of temperature DPS in large-scale vertical quench furnace

Since large-scale vertical quench furnace is voluminous,whose working condition is a typically complex process with distributed parameter,nonlinear,multi-inputs/multi-outputs,close coupled variables,etc,dynamically decoupling control algorithm of temperature distributed parameter system in the furnace was presented,by which the whole system was decoupled to several subsystems and the implementation of controller was simplified.With finite difference approximation,the space and time step size was solved to ensure the convergency of finite difference approximation.After decoupling,the subsystems were controlled with self-learning PID control algorithm.The results show that the temperature control precision and homogeneity are improved;the overshoot and process in temperature rising period are reduced simultaneity.The uniformity of axial temperature distribution increases from -6—6 ℃ to -2—2 ℃;the rising period decreases from 40 min to 25 min,and the overshoot decrease from 15 ℃ to 7 ℃.