Intelligent Modeling and Predictive Control of Pre-Grinding System

Stably controlling the pre-grinding process is paramount important for improving the operational efficiency and significantly reducing production costs in cement plants. Recognizing the complexity in both structure and operation of the pre-grinding process, this paper proposed a fuzzy and model predictive control system to stabilize and optimize the pre-grinding process. Based on the available techniques and system analysis, it is divided into two different sub-systems. One is handled by Fuzzy Logic Control (FLC), and the other is implemented by Linear Matrix Inequality (LMI)-based Model Predictive Control (MPC) based on the model achieved by Least Square Support Vector Machine (LS-SVM) regression. With this approach, the control parameters can be obtained online by the use of aforementioned algorithms and applied to the pre-grinding system by using OLE for Process Control (OPC) and relevant software. The trail system has been deployed in the field and its operation clearly demonstrates the effectiveness and feasibility of this control system in practice.

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