Iterative learning based particle size distribution control in grinding process using output PDF method

This paper presents an Iterative Learning Control (ILC) algorithm to improve the control performance of ball milling process batch by batch, where the output PDF method is adopted in each batch. Firstly, the ball milling process is modeled based on Population Balance Equations with first-order breakage functions. Secondly, output PDF method is adopted within each batch to make the particle size distribution follow a target one as close as possible. An ILC algorithm is developed to tune the parameters of basis functions based on Gradient Descent Method. Finally, simulation results are presented where control performance is improved.