Soft Constrained MPC Applied to an Industrial Cement Mill Grinding Circuit

G. Prasath, M. Chidambaram, B. Recke, J. B. Jørgensen

Abstract

Cement mill grinding circuits using ball mills are used for grinding cement clinker into cement powder. They use about 40% of the power consumed in a cement plant. In this paper, we introduce a new Model Predictive Controller (MPC) for cement mill grinding circuits that improves operation and therefore has the potential to decrease the specific energy consumption for production of cement. The MPC is based on linear models that are identified using step tests. The key novelty in the MPC is that it uses soft constraints to form a piecewise quadratic penalty function with a dead zone. The MPC with this penalty function mitigates the effect of large inevitable uncertainties in the identified models for cement mill grinding circuits. The new MPC accommodates plant-model mismatch and provides better control than conventional MPC and fuzzy controllers. This is demonstrated by simulations using linear systems, simulations using a detailed cement grinding circuit simulator, and by tests in an industrial cement mill grinding circuit.

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Reference

G. Prasath, M. Chidambaram, B. Recke, J.B. Jørgensen: “Soft Constrained MPC Applied to an Industrial Cement Mill Grinding Circuit”, submitted to Control Engineering Practice, November 2017