No abstract

This paper presents the design of a fractional controller, which is applied to a fractional MISO model for cement rotary kiln. The designed controller is a combination of a fractional PID and a Linear Quadratic Regulator (LQR), where the proportional action of fractional PID is replaced by the LQR gain matrix. In addition, we evaluated the criteria of robustness of the controller, such as gain margin; phase margin; robustness to disturbances; sensitivity and rejection of high frequency noise, applied to the entire model (plant-controller).

How to cite this article: HERNÁNDEZ, O. D.; QUIROZ, J., and ORTIZ VALENCIA, P. A. Combustion system model of a wet process Clinker kiln. Ingeniería y Universidad. 2014, vol. 18, no. 2, pp. 329-353. http AbstractThis paper presents the model of the combustion process of a clinker kiln, which is obtained from an energy balance represented in the heat generated by burning coal and how this is distributed across the process. Data comes from the actual process variables, obtained from the control system using OLE for Process Control, which operates using experimental data and variables that are assumed to be constant. The resulting model is fitted with two tools: least squares and Infinite Impulse Response filter of first order. It validates and verifies the model and its settings using two statistical tools: box and whisker diagram and method of eight statistical metrics related by a fuzzy function. The use of these tools evidence satisfactory performance of the proposed model. KeywordsKiln; energy balance; least squares; IIR filters; clinker ResumenEn este trabajo se presenta el modelo del proceso de combustión de un horno rotatorio de Clinker, el cual se obtiene a partir de un balance de energía representado en el calor que se genera por la combustión de carbón y la forma como se distribuye aquel en todo el proceso. Se utilizan datos de las variables reales del proceso, obtenidas del sistema de control mediante OLE for Process Control, las cuales se operan con datos experimentales y variables que se asumen como constantes. El modelo obtenido se ajusta con dos herramientas: mínimos cuadrados y filtro Infinite Impulse Response de primer orden. Se valida y comprueba el modelo y sus ajustes utilizando dos herramientas estadísticas: diagrama de cajas y bigotes y un método de ocho métricas estadísti-cas relacionadas por una función difusa. La utilización de estas herramientas evidencia un desempeño satisfactorio del modelo planteado. Palabras clave