A simulation- and model-based approach to PI control pairing and tuning for the pyro process in a cement plant

TL;DR

This paper presents a simulation-based method for designing and tuning decentralized PI controllers for the pyro process in cement plants, enhancing energy efficiency and sustainability.

Contribution

It introduces a novel DAE model for the pyro process and applies RGA and IMC techniques for optimal controller pairing and tuning.

Findings

PI controllers with IMC tuning outperform manual tuning in response speed and smoothness.

The DAE model effectively simulates the pyro process dynamics.

RGA helps in optimal pairing of control variables.

Abstract

The operation of the pyro process in cement production significantly affects the energy efficiency and sustainability of the cement plant, especially for reductions in carbon dioxide emissions. Hence, pyro process control is essential to obtain efficient and sustainable operation of cement plants. In this paper, we demonstrate how simulations and models can be utilized to evaluate and design control strategies for the pyro section in cement plants. We apply a novel differential algebraic equation (DAE) model for dynamic simulation of the pyro-section in cement plants to design decentralized PI controllers for the pyro-section. We utilize the pyro-process model to evaluate the control structure design. Through linearization of the pyro-process model, we apply the Relative Gain Array (RGA) method to choose and evaluate the pairings of the manipulated variables (MVs) and the controlled variables (CVs). Using simulations of the pyro-section, we generate step responses to estimate transfer models and apply Internal Model Control (IMC) for the tuning of the individual decentralized single-input single-output (SISO) PI controllers. Closed-loop simulations of the PI controllers demonstrate that PI controllers with IMC parameters provide smoother and faster responses compared with manually tuned PI parameters.