Research On Model Predictive Control Algorithm Of Dynamic Batching Process Based On Discrete Element Method

In the process of refined production process,the batching process as pre-processing process on the final production results plays a vital role,which determines the quality of industrial product.How to achieve rapid batching process while ensuring the batching accuracy has always been a major difficulty in the current industrial production process.At present,there are many problems exist in dynamic batching process such as the bulk density of material is non-uniform and time delay in system operating.These problems result in low batching accuracy and cannot achieve high accuracy control requirement of material flow.Time delay system with disturbance is always a hot topic in control field.Taking dynamic batching system in the production line of a building materials enterprise as research background,this paper researched the control algorithm of time delay with disturbance batching process.This paper started from the analysis of technological process.The basic equipment used in the production process and the main factors influencing the precision of the dynamic batching were analyzed,thus establishing a dynamic batching system model.In order to analyze the effect of material bulk density fluctuation on batching accuracy,this paper built a simulation platform of dynamic batching system in discrete element simulation software EDEM,and the set value of discrete element simulation parameters are obtained by analyzing the dynamic batching data.With a set of discrete element simulation experiments designed,this paper obtained the law of bulk density fluctuation from analyzing mass flow data in the simulation experiment.At the same time,in order to control actual material mass flow more timely,this paper controlled the hopper height and the feeding belt velocity simultaneously.This paper utilized regression analysis method to obtained the relationship between hopper height and feeding belt velocity.Thus,the dynamic batching system was considered as a SISO system.According to the fluctuation of bulk density in the dynamic batching process,this paper utilized open-loop transfer function and material bulk density fluctuation together to describe the controlled object.Then,aiming at the characteristics of the open-loop transfer function and material bulk density fluctuation,a generalized predictive control algorithm was designed by using model predictive control technique.Programming this generalized predictive control in MATLAB and simulating analysis,the results showed that the proposed generalized predictive control algorithm had good robustness and followability.More importantly,this dynamic batching GPC algorithm can meet the high-precision batching requirements which demand the batching ratio improved to ?3%.In summary,this paper can provide theoretical basis and model reference for the research of dynamic batching process in industrial production.