Non-linear models for a gypsum kiln. A comparative analysis

INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL. WORLD CONGRESS (15.2002.BARCELONA)This paper presents several non-linear models adjusted in order to capture the dynamics of a gypsum kiln. The behavior of this kind of processes is affected by nonlinear effects caused by the existence of disturbances and the coupling among some variables. The use of second order Volterra and Hammerstein models as appropriate solutions to describe the process dynamics is analyzed. A thorough study of the best model order and structure is performed. Coefficients that best fit real data are also selected. This work aims to obtain a good non-linear model in order to implement a non-linear predictive controller, able to improve the performances of those linear controllers already tested on the plant.Comisión Interministerial de Ciencia y Tecnología (CICYT) 1FD97-083

Volterra Model Based Predictive Control, application to a Pem Fue Cell

14th Nordic Process Control Workshop - Espoo, Finland Duration: 23 Aug 2007 → 25 Aug 2007This paper presents a non linear model predictive controller for a PEM fuel cell for which the starvation control is the main objective. A second order Volterra model for control is obtained using input/output data for which the power supplied by the fuel cell is considered as a measurable disturbance. The controller developed allows to solve the nonlinear objective function in a way that it can be actually implemented in fast systems like Fuel cells. The use of a nonlinear controller is justified while comparing the outcome obtained with a linear controller of the same class

The Assessment of the Aesthetic Damage of Scars by Various Coroners from Different Institutes of Legal Medicine

Una de las actividades de mayor importancia en la medicina forense práctica es la valoración del daño corporal. Dentro de la misma, en ocasiones, el médico forense se enfrenta a la difícil tarea de tener que valorar el daño o perjuicio estético que ocasionan cicatrices resultantes de agentes externos, valoración no exenta de un gran componente de subjetividad. Presentamos un estudio de la valoración que de cuatro cicatrices, resultantes de sendos accidentes de tráfico, han efectuado médicos forenses de los Institutos de Medicina Legal de Cataluña, Alicante y Galicia siguiendo las reglas de utilización de la tabla VI del Sistema para la valoración de los daños y perjuicios causados a las personas en accidentes de circulación (RD Legislativo 8/2004).Se ha utilizado una metodología descriptiva (medidas de tendencia central, de dispersión y de forma) y un análisis estadístico con pruebas no paramétricas. Se han obtenido puntuaciones medias en el Instituto de Medicina Legal de Cataluña en las cuatro cicatrices sometidas a valoración inferiores a las del Instituto de Medicina Legal de Alicante y del Instituto de Medicina Legal de Galicia. No se han encontrado diferencias entre las medidas de tendencia central en las valoraciones efectuadas por los médicos forenses de los tres Institutos de Medicina Legal al nivel de significación utilizado de a = 0.05 para los casos B y C mientras que para los casos A y D se han hallado diferencias estadísticamente significativas entre las medianas de las valoraciones efectuadas por los médicos forenses de los IML de Cataluña, Alicante y Galicia.One of the most important activities in forensic practice is the assessment of bodily harm. Within this field, the medical examiner sometimes faces the difficult task of having to assess damage or disfigurement resulting from scars caused by external agents. This assessment is not without a large element of subjectivity. We present a study of the assessment of four scars, from two separate traffic accidents, carried out by coroners from the Institute of Legal Medicine of Catalonia, Alicante and Galicia following the rules of Table VI using the System for assessing the damages caused to people in road accidents (RDL 8/2004). We used a descriptive methodology (measures of central tendency, dispersion and form) and statistical analysis with nonparametric tests. Mean scores were obtained at the Institute of Legal Medicine of Catalonia in the four inferior valuation of scars at the Legal Medicine Institute of Alicante and the Institute of Legal Medicine of Galicia. No differences were found between measures of central tendency of assessments by medical examiners of the three Institutes of Legal Medicine at the significance level of a = 0.05 used for cases B and C while for cases A and D statistically significant differences between the medians of the assessments made by the medical examiner of the Institute of Legal Medicine of Catalonia, Alicante and Galicia have been found

The assessment of aesthetic injury by scars by different groups

La valoración del daño o perjuicio estético que ocasionan las cicatrices resultantes de accidentes de tráfico es una tarea no exenta de un gran componente de subjetividad. Presentamos un estudio de la valoración que de cuatro cicatrices, resultantes de sendos accidentes de tráfico, siguiendo las reglas de utilización de la tabla VI del Sistema para la valoración de los daños y perjuicios causados a las personas en accidentes de circulación (RD Legislativo 8/2004), han efectuado tres colectivos encuestados de diferentes procedencias: “jurídico” (Magistrados-Jueces y Jueces, Fiscales, abogados con ejercicio profesional en el ámbito de compañías de seguros o en el ámbito privado y estudiantes de la Escuela de Práctica Jurídica), “peritos médicos” (médicos forenses y médicos valoradores del daño corporal) y “resto de población” (estudiantes universitarios de Bellas Artes, sanitarios no médicos y otros estudiantes universitarios). Se han recogido 448 encuestas procedentes de estos tres colectivos en las que puntuaban el daño estético siguiendo la tabla VI. Se ha utilizado una metodología descriptiva y un análisis estadístico con pruebas no paramétricas. Se han encontrado diferencias estadísticamente significativas entre las valoraciones del perjuicio estético realizadas por los tres colectivos profesionales sometidos a encuesta: jurídico, peritos médicos y resto de población, al nivel de significación de α = 0.05. Los peritos médicos (médicos forenses y médicos valoradores del daño corporal) han valorado las cicatrices muy por debajo del colectivo jurídico, y éste a su vez, algo por debajo del resto de población.The assessment of damage or disfigurement caused by scars resulting from accidents is a task that inevitably involves a certain degree of subjectivity. We present a study of the assessment of four scars resulting from traffic accidents, according to the rules of use of Table VI of the system for the assessment of damages caused to people in traffic accidents (RDL 8/2004). The assessment was carried out by three groups of different origins: "legal professionals" (Judges, prosecutors, lawyers from the area of insurance companies or the private sector and students of the School of Legal Practice), "medical experts" (forensic doctors and doctors of the assessment of bodily harm) and other members of the population (students of fine art, other healthcare staff who are not doctors and other university students). 448 surveys were collected in from the three groups in which they gave a numerical value to the aesthetic damage based on Table VI. We used a descriptive methodology and statistical analysis using nonparametric tests. Significant statistical differences between the assessments of aesthetic damage carried out by the three professional groups in the survey were found: legal, medical experts and other members of the population, were found with a level of significance of α = 0.05. The medical experts (forensic doctors and medical assessors of bodily harm) rated the scars well below the level of the legal experts and at the same time they rated them below the level of the rest of the population

Optimisation of Operator Support Systems through Artificial Intelligence for the Cast Steel Industry:A Case for Optimisation of the Oxygen Blowing Process Based on Machine Learning Algorithms

The processes involved in the metallurgical industry consume significant amounts of energy and materials, so improving their control would result in considerable improvements in the efficient use of these resources. This study is part of the MORSE H2020 Project, and it aims to implement an operator support system that improves the efficiency of the oxygen blowing process of a real cast steel foundry. For this purpose, a machine learning agent is developed according to a reinforcement learning method suitable for the dynamics of the oxygen blowing process in the cast steel factory. This reinforcement learning agent is trained with both historical data provided by the company and data generated by an external model. The trained agent will be the basis of the operator support system that will be integrated into the factory, allowing the agent to continue improving with new and real experience. The results show that the suggestions of the agent improve as it gains experience, and consequently the efficiency of the process also improves. As a result, the success rate of the process increases by 12%

Steelmaking Process Optimised through a Decision Support System Aided by Self-Learning Machine Learning

This paper presents the application of a reinforcement learning (RL) algorithm, concretely Q-Learning, as the core of a decision support system (DSS) for a steelmaking subprocess, the Composition Adjustment by Sealed Argon-bubbling with Oxygen Blowing (CAS-OB) from the SSAB Raahe steel plant. Since many CAS-OB actions are selected based on operator experience, this research aims to develop a DSS to assist the operator in taking the proper decisions during the process, especially less experienced operators. The DSS is intended to supports the operators in real-time during the process to facilitate their work and optimise the process, improving material and energy efficiency, thus increasing the operation’s sustainability. The objective is that the algorithm learns the process based only on raw data from the CAS-OB historical database, and on rewards set according to the objectives. Finally, the DSS was tested and validated by a developer engineer from the CAS-OB steelmaking plant. The results show that the algorithm successfully learns the process, recommending the same actions as those taken by the operator 69.23% of the time. The algorithm also suggests a better option in 30.76% of the remaining cases. Thanks to the DSS, the heat rejection due to wrong composition is reduced by 4%, and temperature accuracy is increased to 83.33%. These improvements resulted in an estimated reduction of 2% in CO2 emissions, 0.5% in energy consumption and 1.5% in costs. Additionally, actions taken based on the operator’s experience are incorporated into the DSS knowledge, facilitating the integration of operators with lower experience in the process