Support vector machine model based predictive pid control system for cement rotary kiln

The rotary kiln calcination is the most important part of cement production including complicated physical and chemical reaction processes with large inertia, pure hysteresis, nonlinearity and strong coupling characteristics. Considering the need of advanced process control in cement industry, this paper presents the application of support vector machine modeling and generalized predictive control PID control algorithm to the conventional cement production. The main control system structure includes three control loops as the pressure control loop, the burning zone control loop and the back-end of kiln temperature control loop. Based on the analysis of PID and generalized predictive control algorithm, the performance index of generalized predictive control algorithm is restructured into PID form. By analysis of the experimental data, the nonlinear regression model based on SVM is introduced. The control algorithm using SVM model is simulated in two cases to derive the responses of system compared with the ordinary PID control algorithm. The simulation results show the effectiveness of the control and modeling scheme with better response time and small temperature deviation.