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.