The Research And Application Of Predictive Control On Calcination System In Jidong C Line

In the process of cement production, the clinker calcination process of the cementkiln is a complex thermal reaction process in which some physical and chemicalrelationship is not very clear, and has serious nonlinear and time-varying characteristics.In addition, the detection of some parts is also limited by the high temperature, dust andspace. So, there is a lack of the ideal mathematical model to describe it comprehensivelyand accurately. The intelligent optimization control of the cement rotary kiln clinkercalcination process can ensure the balanced and stable production and the safe operationof the equipment, so that the production process is ofen at its best, achieving thehigh-quality, efficient and low consumption purpose. At present, the cement rotary kilncalcination systems’ closed-loop control circuit of the domestic large and medium cemenplant is still commonly used traditional PID control, mainly relys on the experience of theoperator, so the parameters are difficult to tune, the control effect is not ideal. For thecomplex mechanism of the cement rotary kiln calcination process, the topic proposes thepredictive control method based on hybrid model which through the ingeniouscombination of predicted output and optimization algorithms, rolling forecasts reasonableinput, thus achieve the intelligent automatic control.In this paper,the main research worksare as follows:First of all, introduce the dry process cement production which is the object of thispaper, focusing on the stage process of cement calcining. According to the the analysis ofthe cement production process and principles of physical and chemical changes in variousstages,Combined the Jidong Cement feedback and control of the site, Using the amountof feed coal and baffle opening of kiln fan as the main operating variables, and using thetemperature of the rotary kiln and the oxygen content in the rotary kiln as the targetvariable of the control, so we can establish the predictive control model of cement rotarykiln.Then, using Hybrid model to control cement rotary kiln calcination system whichtake the overall rotary kiln control system as two parts: the steady state model and dynamic model, the data collected at the scene is analysised and processed as steady-statedata and dynamic data. using the the RBF algorithm to Identificate the steady-state data ofthe rotary kiln calcination system to obtain the steady-state model of nonlinear neuralnetwork system, To the dynamic data using the least squares method to identificate thesystem obtain a linear ARX model. The Hybrid model is gained by real-time adjustment tothe steady-state and dynamic models.To intelligent control we take the form of rollingoptimization and sequential quadratic programming method prediction estimates, based onthe characteristics of the Hybrid model and forecast output.Finally, based on RBF-ARX Hybrid model and predict control algorithm designe thedata processor, the model identification and the predictive controller for MIMO systemlike cement rotary kiln calcination process. OPC technology is taken for data exchangeand communication from this intelligent controller to the field of DCS system lower. TheHybrid model based predictive control method is applied in the cement rotary kilncalcination control of the Jidong cement third phase C line, proved advanced and practicalby comparation.