Research On Control Strategy Of Ball Mill Based On Brain Emotion Learning Model

Ball mill coal pulverizing system is the key equipment in the process of material crushing and has been widely used in electric power, mining, metallurgy, and cement industries. It runs high safety coefficient, the suitable quantity of coal, but it also has the large amount of energy consumption. The running state of the ball mill can directly affect the economic benefit and whether it can be safe and stable production, however, it’s difficult to achieve the automatic control in the traditional control method since the ball mill is a multivariable, nonlinear, large delay, large inertia complex controlled object. Therefore, it has irreplaceable engineering value and practical significance to realize the intelligent control of the steel ball coal mill system.Brain emotional learning(BEL) model are good at learning regulating and generalization as a new type of bionic calculation model base on physiologically. In recent years, the BEL model and on the basis of the intelligent controller has been widely attention and application. In view of this, this paper focus on the identification and control of ball mill on the system, using the BEL model identification and the corresponding control algorithm design, the main work done is as follows:(1) An in-depth study of the basic structure and operation mechanism of ball mill. To explore the domestic and foreign existing control methods and strategies, describes the basic control of ball mill is required, the important value and significance to improve the degree of automation is introduced, the relationship between input and output and the object characteristics of ball mill system, the establishment of mathematical model of ball mill is analyzed in detail.(2) Analysis of the brain emotional learning model of the background, application status and development prospects. Study on the brain emotional learning weight model of special regulation rules and intelligent controller based on BEL model, on this basis, in the Matlab software under the Simulink platform, a simulation platform is established BEL model, provides a good experimental platform for the research of this topic.(3) The design of the ball mill BEL model identification algorithm based on parameters optimization of PSO. The algorithm is used to optimize the parameters of BEL model and the optimization model for ball mill system identification by using PSO optimization, effectively improve the accuracy of ball mill system mathematical model, the identification model can output accurate tracking system.(4) For multi input multi output characteristics of ball mill, based on the BEL model identification algorithm on the optimization design of PSO, using the BEL model to complete the internal model controller for ball mill, put forward the BEL model based on internal model control algorithm, and the simulation experiments, the internal model control method to the Biao Mingji BEL model with a strong robustness, anti-jamming capability and other advantages.