In this work an advanced control system design aimed to the improvement of economic benefits and control performances of a cement rotary kiln located in an Italian cement plant is discussed. A Model Predictive Controller, together with other functional blocks designed to manage normal and critical situations, constitutes the core of the proposed strategy. Accurate identification procedures, aimed at obtaining accurate dynamical process models, have been performed. | Journal of Automation and Control Engineering Vol. 4, No. 4, August 2016 Improving Performances of a Cement Rotary Kiln: A Model Predictive Control Solution Silvia Maria Zanoli, Crescenzo Pepe, and Matteo Rocchi UniversitàPolitecnica delle Marche, Ancona, Italy Email: {, }@ Abstract—In this work an advanced control system design aimed to the improvement of economic benefits and control performances of a cement rotary kiln located in an Italian cement plant is discussed. A Model Predictive Controller, together with other functional blocks designed to manage normal and critical situations, constitutes the core of the proposed strategy. Accurate identification procedures, aimed at obtaining accurate dynamical process models, have been performed. A suited cooperation of system modules and an ad hoc design of each of them allowed the meeting of control specifications, the increase of system reliability and the reduction of the standard deviation of critic process variables. In this way, the system can more safely operate closer to its operative bounds. The implementation of the proposed control system on a real plant has proven its soundness, leading to improvements in terms of energy efficiency, product quality and environmental impact, compared to the previous control system. Index Terms—cement rotary kiln, advanced process control, model predictive control, economic optimization, environmental emissions, process control I. INTRODUCTION In today’s world, cement is the substratum for civil engineering and its applications. The world cement production has grown in a constant manner since the early ‘50s. In particular, in recent decades, there was an increasing need for innovations in the production chain, as well as an increased need for a high level of automation, also due to the complex chemical and physical processes involved [1]. In this context may be placed the process control optimization, which, by using advanced control .
