Simple Tuning Rules for Feedforward Compensators Applied to Greenhouse Daytime Temperature Control Using Natural Ventilation

In this work, simple tuning rules for feedforward compensators were applied to design a control strategy to regulate the inside air temperature of a greenhouse during daytime by means of a natural ventilation system. The developed control strategy is based on a PI (Proportional-Integral) controller combined with feedforward compensators to improve the performance against measurable external disturbances such as outside air temperature, solar radiation, and wind velocity. Since the greenhouse process dynamics is very complex and physical non-linear models are mathematically complicated, a system identification methodology was proposed to obtain simpler models (high-order polynomial and low-order transfer functions). Thus, an easier procedure was completed to tune the PI controller parameters and to obtain the feedforward compensators expressions by following a series of modern and simple tuning rules. Simulations with real data were executed to compare the control performance of a PI controller with or without the addition of feedforward compensators. Moreover, real tests for the developed control strategy were carried out in an experimental greenhouse. Results demonstrate an enhanced control performance with the presence of the feedforward compensators under different weather condition

Análise e desenvolvimento de controladores das variáveis ambientais de uma estufa agrícola

TCC (graduação) - Universidade Federal de Santa Catarina. Centro de Ciências, Tecnologias e Saúde. Engenharia de Energia.Ao longo da história, as variações do clima sempre trouxeram mudanças na forma como a humanidade maneja a sua produção de alimentos. O cultivo protegido é considerado como uma das formas mais sofisticadas de produção atualmente, pelo fato de criar condições favoráveis para que as plantas possam desenvolver todo seu potencial genético. O presente trabalho tem por objetivo analisar um modelo matemático que descreve o comportamento térmico de uma estufa agrícola, bem como projetar e avaliar técnicas de controle que possibilitem um melhor manejo no uso dos recursos naturais. Diferentes cenários referentes às condições ambientais foram avaliados através do modelo matemático, permitindo propor estratégias de controle adequadas de acordo com as necessidades específicas de cada cultura. As técnicas de controle avaliadas apresentaram bons resultados, indicando que as mesmas são adequadas para este tipo de sistema térmico. As pesquisas relacionadas a este tema tornam-se fundamentais para que novas tecnologias sejam desenvolvidas, permitindo um aperfeiçoamento nas técnicas de produção em cultivo protegido.Throughout history, climate variations have always brought changes in the way that mankind manages the food production. Protected cultivation is considered one of the most sophisticated forms of production today, because it creates favorable conditions for plants to develop their full genetic potential. The present work aims to analyze the mathematical model that describes the thermal behavior of an agricultural greenhouse, as well as to design and evaluate control techniques that allow a better management in the use of natural resources. Several climate condition scenarios are evaluated using the equations of the mathematical model, allowing to propose adequate control strategies according to the needs of each crop. The control techniques evaluated presented good results, indicating that they are suitable for this type of thermal system. The research related to this topic becomes essential for the development of new technologies, allowing an improvement in the techniques of production in greenhouses

Control predictivo basado en modelos mediante técnicas de optimización heurística. Aplicación a procesos no lineales y multivariables

La Tesis Doctoral se fundamenta, principalmente, en la exploración de nuevos métodos de Control Predictivo Basado en Modelos (MBPC) mediante la incorporación de herramientas de optimización heurística y las mejoras en las prestaciones que se pueden conseguir con ello. La metodología de MBPC constituye un campo cada vez más importante en el control de procesos debido a que se trata de una formulación muy intuitiva, y a la vez muy potente, de un problema de control (por tanto es más fácilmente aceptable en el ámbito industrial). A pesar de ello, presenta limitaciones cuando se quiere aplicar a ciertos procesos complejos. Un elemento fundamental y al mismo tiempo limitante de ésta metodología lo constituye la técnica de optimización que se utilice. Simplificando mucho, el MBPC se convierte en un problema de minimización en cada periodo de muestreo, y la complejidad del problema de control se refleja directamente en la función a minimizar en cada instante. Si se incorporan modelos no lineales, restricciones en las variables, e índices de funcionamiento sofisticados, todo ello asociado a los problemas de tiempo real, se va a requerir algoritmos de optimización adecuados que garanticen el mínimo global en un tiempo acotado. En este sentido, la tesis incluye un análisis de las metodologías de Optimización Heurísticas, Simulated Annealing y Algoritmos Genéticos, como candidatas a la resolución de ese tipo de problemas y apartir de ellas realiza una implementación novedosa (denominada ASA) dentro del grupo de los algoritmos de Simulated Annealing que reduce el coste computacional. En los Algoritmos Genéticos, se obtienen las combinaciones de codificación y operadores genéticos más adecuadas para conseguir buenas relaciones de 'calidad de la solución/coste computacional' en la resolución de problemas de minimización complejos (no convexos, con discontinuidades, restricciones, etc.). Todo este análisis previo, permite la adaptación adecuada de estas técnicas heurísticas......Blasco Ferragud, FX. (1999). Control predictivo basado en modelos mediante técnicas de optimización heurística. Aplicación a procesos no lineales y multivariables [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/15995Palanci

Biomass for Energy Country Specific Show Case Studies

In many domestic and industrial processes, vast percentages of primary energy are produced by the combustion of fossil fuels. Apart from diminishing the source of fossil fuels and the increasing risk of higher costs and energy security, the impact on the environment is worsening continually. Renewables are becoming very popular, but are, at present, more expensive than fossil fuels, especially photovoltaics and hydropower. Biomass is one of the most established and common sources of fuel known to mankind, and has been in continuous use for domestic heating and cooking over the years, especially in poorer communities. The use of biomass to produce electricity is interesting and is gaining ground. There are several ways to produce electricity from biomass. Steam and gas turbine technology is well established but requires temperatures in excess of 250 °C to work effectively. The organic Rankine cycle (ORC), where low-boiling-point organic solutions can be used to tailor the appropriate solution, is particularly successful for relatively low temperature heat sources, such as waste heat from coal, gas and biomass burners. Other relatively recent technologies have become more visible, such as the Stirling engine and thermo-electric generators are particularly useful for small power production. However, the uptake of renewables in general, and biomass in particular, is still considered somewhat risky due to the lack of best practice examples to demonstrate how efficient the technology is today. Hence, the call for this Special Issue, focusing on country files, so that different nations’ experiences can be shared and best practices can be published, is warranted. This is realistic, as it seems that some nations have different attitudes to biomass, perhaps due to resource availability, or the technology needed to utilize biomass. Therefore, I suggest that we go forward with this theme, and encourage scientists and engineers who are researching in this field to present case studies related to different countries. I certainly have one case study for the UK to present

Computational Optimizations for Machine Learning

The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity

Recent Development of Hybrid Renewable Energy Systems

Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)

Z-Numbers-Based Approach to Hotel Service Quality Assessment

In this study, we are analyzing the possibility of using Z-numbers for measuring the service quality and decision-making for quality improvement in the hotel industry. Techniques used for these purposes are based on consumer evalu- ations - expectations and perceptions. As a rule, these evaluations are expressed in crisp numbers (Likert scale) or fuzzy estimates. However, descriptions of the respondent opinions based on crisp or fuzzy numbers formalism not in all cases are relevant. The existing methods do not take into account the degree of con- fidence of respondents in their assessments. A fuzzy approach better describes the uncertainties associated with human perceptions and expectations. Linguis- tic values are more acceptable than crisp numbers. To consider the subjective natures of both service quality estimates and confidence degree in them, the two- component Z-numbers Z = (A, B) were used. Z-numbers express more adequately the opinion of consumers. The proposed and computationally efficient approach (Z-SERVQUAL, Z-IPA) allows to determine the quality of services and iden- tify the factors that required improvement and the areas for further development. The suggested method was applied to evaluate the service quality in small and medium-sized hotels in Turkey and Azerbaijan, illustrated by the example

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity