Modeling and control of ball mill system considering coal moisture

Abstract This study analyzes the dynamic characteristics of duplex inlet and outlet ball mill direct firing pulverizing system. A mass and energy balance-based model is built by thermodynamic analysis. As a critical parameter in pulverized coal humidity control, coal moisture is considered in the mechanism model, and an extended Kalman filter is designed to estimate the coal moisture. A multivariable control system is designed using extended state space predictive controller. The dynamic characteristic of the mill can be effectively forecasted using the established model. The system can rapidly track unit load changes while reducing the disturbance caused by coal moisture and other outlets.

[1]  Jan Dimon Bendtsen,et al.  Derivation and validation of a coal mill model for control , 2009 .

[2]  Peter Fogh Odgaard,et al.  Observer-based fault detection and moisture estimating in coal mills , 2008 .

[3]  Jong-Min Lee,et al.  Application of near infrared diffuse reflectance spectroscopy for on-line measurement of coal properties , 2009 .

[4]  Yuan Gang,et al.  Research of Mathematical Model of the Ball Mill with Double Inlets and Outlets , 2008, 2008 International Conference on Intelligent Computation Technology and Automation (ICICTA).

[5]  S. Chehreh Chelgani,et al.  Simultaneous prediction of coal rank parameters based on ultimate analysis using regression and artificial neural network , 2010 .

[6]  Marko Bacic,et al.  Model predictive control , 2003 .

[7]  Tianyou Chai,et al.  Multiple models and neural networks based decoupling control of ball mill coal-pulverizing systems , 2011 .

[8]  Duan Yong.  Fuzzy neural network modeling and simulation of BBD ball mill , 2009 .

[9]  Jan Poland,et al.  Nonlinear coal mill modeling and its application to model predictive control , 2013 .

[10]  Xie Xie.  Heat Value Measurement of Coal Fuel for a Once-through Boiler , 2012 .

[11]  Jizhen Liu,et al.  Modelling and control of pulverizing system considering coal moisture , 2015 .

[12]  Mohammad Farrokhi,et al.  State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF , 2010, IEEE Transactions on Industrial Electronics.

[13]  Kazuhiko Fujiwara,et al.  Estimation of water content in coal using terahertz spectroscopy , 2013 .

[14]  Jizhen Liu,et al.  Soft sensing of coal moisture , 2015 .

[15]  Q.H. Wu,et al.  Development of a Multisegment Coal Mill Model Using an Evolutionary Computation Technique , 2007, IEEE Transactions on Energy Conversion.