The Generalized Predictive Control Software For The Electric Current Of Cement Grinding Mill Elevator

As an important equipment of cement grinding system, mill bears the task of material grinding. In the process of cement production, the production efficiency of grinding system and the quality of cement products are closely related to the condition of mill load. If the mill load is smaller, it may reduce the production efficiency of grinding system. If the mill load is larger, it may lead to overage grind and cause a decline in the quality of cement products. Therefore, it is a problem to be solved urgently to ensure the machine load stability.Based on the joint cement clinker grinding system of some group as the research object, in the completion of the production process to analyze and summarize the experience of experts, the control scheme combining the recursive least square method with forgetting factor and the generalized predictive control algorithm is proposed, and developing the generalized predictive control software for the electric current of cement grinding mill elevator. The work of this paper is organized as follows:(1) In order to realize the optimal control of the mill load, the key variable affecting the mill load are analyzed and determined, and proposes the overall design of the software. In ball mill load based on the steady working, by modifying a variable, and the variation tendency of other variables of observation and analysis, the selection came rotating speed of the powder and the grinding of hoist machine between the current relationship can effectively reflect the mill load. Determined by the rotating speed of the powder selecting machine control, grinding machine lifting current is controlled the amount of single input single output control system, and the control software is divided into three parts, data acquisition module and algorithm module and user interface module to achieve.(2) Based on the key of variables(1), the speed of the powder selecting machine and the output current of the mill are used as the input and output data. To realize the predictive control of the current of the mill, it is needed to establish the mathematical model of mill load. Considering the large number of interference factors, first of all, the input and output data of the mean filter processing, to ensure the reliability of the data. Secondly, the model of mill load is identified by using the recursive least square method with forgetting factor, and the optimal model structure is established according to the model error. Finally, based on the model structure of mill load, the generalized predictive control algorithm is used to optimize the current of the mill. By analyzing the simulation results, it is proved that the control algorithm can effectively control the current of the grinding machine to the set value, which lays a theoretical foundation for the realization of the predictive control software.(3) Considering the engineering application of predictive control software development. On the basis of(2), the algorithm module is designed from three aspects: the generation of predictive control algorithm.NET component, the call of.NET component and the interaction between C# and MATLAB data. Because the algorithm module is based on input and output data, to realize the optimal control of the grinding machine to enhance current, and control software running, also need to control the effect of real-time display. Design of the data acquisition module and the user interface from the three aspects of the work process, interface design and program design based on the control requirements, completed the predictive control software development.(4) In order to verify the effectiveness of the predictive control software, based on the completion of(3), using the OPC technology to write the historical data to the DCS control system, to realize the reduction of the operation status of the field. Operation control system from the data acquisition, the predictive control and the trend shows the three aspects of the running software verification, and draws the conclusion that the software can effectively control the grinding of hoist machine current approaches to the setting value, the mill load condition is stable.