Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.

Dynamic control of a reconfigurable stair-climbing mobility system

Electric-powered wheelchairs improve the mobility of people with physical disabilities, but the problem to deal with certain architectural barriers has not been resolved satisfactorily. In order to solve this problem, a stair-climbing mobility system (SCMS) was developed. This paper presents a practical dynamic control system that allows the SCMS to exhibit a successful climbing process when faced with typical architectural barriers such as curbs, ramps, or staircases. The implemented control system depicts high simplicity, computational efficiency, and the possibility of an easy implementation in a microprocessor-/microcontroller-based system. Finally, experiments are included to support theoretical results.

Desarrollo de un sistema automático de medida para el control del consumo en sistemas empotrados

El Grupo de Diseño Electrónico y Microelectrónico de la Universidad Politécnica de Madrid -GDEM- se dedica, entre otras cosas, al estudio y mejora del consumo en sistemas empotrados. Es en este lugar y sobre este tema donde el proyecto a exponer ha tomado forma y desarrollo. Según un artículo de la revista online Revista de Electrónica Embebida, un sistema empotrado o embebido es aquel “sistema controlado por un microprocesador y que gracias a la programación que incorpora o que se le debe incorporar, realiza una función específica para la que ha sido diseñado, integrando en su interior la mayoría de los elementos necesarios para realizar dicho función”. El porqué de estudiar sobre este tema responde a que, cada vez, hay mayor presencia de sistemas empotrados en nuestra vida cotidiana. Esto es debido a que se está tendiendo a dotar de “inteligencia” a todo lo que puedan hacer nuestra vida un poco más fácil. Nos podemos encontrar dichos sistemas en fábricas, oficinas de atención a los ciudadanos, sistemas de seguridad de hogar, relojes, móviles, lavadoras, hornos, aspiradores y un largo etcétera en cualquier aparato que nos podamos imaginar. A pesar de sus grandes ventajas, aún hay grandes inconvenientes. El mayor problema que supone a día de hoy es la autonomía del mismo sistema, ya que hablamos de aparatos que muchas veces están alimentados por baterías -para ayudar a su portabilidad–. Por esto, se está intentando dotar a dichos sistemas de una capacidad de ahorro de energía y toma de decisiones que podrían ayudar a duplicar la autonomía de dicha batería. Un ejemplo claro son los Smartphones de hoy en día, unos aparatos casi indispensables que pueden tener una autonomía de un día. Esto es poco práctico para el usuario en caso de viajes, trabajo u otras situaciones en las que se le dé mucho uso y no pueda tener acceso a una red eléctrica. Es por esto que surge la necesidad de investigar, sin necesidad de mejorar el hardware del sistema, una manera de mejorar esta situación. Este proyecto trabajará en esa línea creando un sistema automático de medida el cual generará las corrientes que servirán como entrada para verificar el sistema de adquisición que junto con la tarjeta Beagle Board permitirá la toma de decisiones en relación con el consumo de energía. Para realizar este sistema, nos ayudaremos de diferentes herramientas que podremos encontrar en el laboratorio del GDEM, como la fuente de alimentación Agilent y la Beagle Board –como principales herramientas de trabajo- . El objetivo principal será la simulación de unas señales que, después de pasar un proceso de conversión y tratado, harán la función de representación del consumo de cada una de las partes que pueden formar un sistema empotrado genérico. Por lo tanto, podemos decir que el sistema hará la funcionalidad de un banco de pruebas que ayudará a simular dicho consumo para que el microprocesador del sistema pueda llegar a tomar alguna decisión. ABSTRACT. The Electronic and Microelectronic Design Group of Universidad Politécnica de Madrid -GDEM- is in charge, between other issues, of improving the embedded system’s consumption. It is in this place and about this subject where the exposed project has taken shape and development. According to an article from de online magazine Revista de Electronica Embebida, an embedded system is “the one controlled by a microprocessor and, thanks to the programing that it includes, it carries out a specific function what it has been designed for, being integrated in it the most necessary elements for realizing the already said function”. The because of studying this subject, answers that each time there is more presence of the embedded system in our daily life. This is due to the tendency of providing “intelligence” to all what can make our lives easier. We can find this kind of systems in factories, offices, security systems, watchers, mobile phones, washing machines, ovens, hoovers and, definitely, in all kind of machines what we can think of. Despite its large vantages, there are still some inconveniences. Nowadays, the most important problem is the autonomy of the system itself when machines that have to be supplied by batteries –making easier the portability-. Therefore, this project is going after a save capacity of energy for the system as well as being able to take decisions in order to duplicate batteries’ autonomy. Smartphones are a clear example. They are a very successful product but the autonomy is just one day. This is not practical for users, at all, if they have to travel, to work or to do any activity that involves a huge use of the phone without a socket nearby. That is why the need of investigating a way to improve this situation. This project is working on this line, creating an automatic system that will generate the currents for verifying the acquisition system that, with the beagle board, will help taking decisions regarding the energy’s consumption. To carry out this system, we need different tools that we can find in the laboratory of the group previously mentioned, like power supply Agilent and the Beagle Board – as main working tools –. The main goal is the simulation of some signals that, after a conversion process, will represent de consumption of each of the parts in the embedded generic system. Therefore, the system will be a testing ground that simulate the consumption, once sent to the processor, to be processed and so the microprocessor system might take some decision.

Personalized rule-based closed-loop control algorithm for type 1 diabetes

Type 1 diabetes-mellitus implies a life-threatening absolute insulin deficiency. Artificial pancreas (CGM sensor, insulin pump and control algorithm) is promising to outperform current open-loop therapies.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

OnToology: An online tool for ontology documentation and evaluation

In this thesis, we designed and implemented an online tool (named "OnToology") to automatically generate documentation and perform evaluation for ontologies. It is also integrated with GitHub version control system to support collaborative environments.