Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.
This paper addresses the control of the blending process in cement industries. This process can be modeled by a nonlinear multivariable system with large parametric uncertainty. Using a specific transformation, a linear parameter varying (LPV) model with set-points as scheduling parameters is developed. Moreover, the model uncertainty originated from the stochastic variation of the composition of the input materials is represented as a polytopic multimodel uncertainty. Then a multivariable gain-scheduled robust controller is designed by convex optimization to control the quality of the raw mix in the blending process. The control performance is illustrated by simulation and compared with a robust controller based on a nominal model.
Maryam Kamgarpour, Luca Furieri, Na Li
Alireza Karimi, Vaibhav Gupta, Elias Sebastian Klauser