Model predictive control for grinding systems

Abstract Grinding systems are modelled, and their models are brought into the form of multivariable impulse response or weighting function matrices. Two predictive control algorithms are developed and tested in the control of two simulated models of grinding systems. Their design is based on the elimination of the steady-state errors, and the decoupling of their interactions. The dynamic interactions cannot be eliminated, but their effects are reduced by the controllers.