Sistema de control de inversor de potencia monofásico por eliminación de armónicos

[ES]Este proyecto consiste en el diseño de un sistema de control integrado para inversores de potencia monofásicos haciendo uso del algoritmo de eliminación de armónicos. De este modo, permite generar una señal de salida con frecuencia controlada, ideal para la alimentación de motores eléctricos monofásicos. El objetivo del mismo es lograr la implementación de un algoritmo de rendimiento superior a las alternativas PWM para casos de frecuencia de salida elevada. El sistema incluye el software y hardware necesario para implementación completa, así como los documentos necesarios para su fabricación en serie.

Diseño del procedimiento para la validación de los equipos de un sistema de control de acceso de RFID pasivo

[ES]En este documento se realiza el diseño de un procedimiento para la validación de los equipos necesarios a la hora de implantar un sistema de control de acceso mediante RFID pasivo. Para ello, se analizarán los distintos tipos de sistemas RFID y se elige uno para la posterior adquisición de los dispositivos necesarios. Se comprobará la normativa vigente ETSI, que regula las emisiones de potencia de los equipos de identificación por radiofrecuencia, y se verificará que se cumplen los requisitos necesarios para implantar el sistema de control de acceso realizando un análisis funcional en situaciones reales.

Stochastic optimal control

H. J. Kushner has obtained the differential equation satisfied by the optimal feedback control law for a stochastic control system in which the plant dynamics and observations are perturbed by independent additive Gaussian white noise processes. However, the differentiation includes the first and second functional derivatives and, except for a restricted set of systems, is too complex to solve with present techniques.

This investigation studies the optimal control law for the open loop system and incorporates it in a sub-optimal feedback control law. This suboptimal control law's performance is at least as good as that of the optimal control function and satisfies a differential equation involving only the first functional derivative. The solution of this equation is equivalent to solving two two-point boundary valued integro-partial differential equations. An approximate solution has advantages over the conventional approximate solution of Kushner's equation.

As a result of this study, well known results of deterministic optimal control are deduced from the analysis of optimal open loop control.

Control de un sistema de accionamientos de traslación basado en correa para un manipulador de cinemática paralela

[ES]Este Trabajo de Fin de Grado “Control de un sistema de accionamientos de traslación basado en correa para un manipulador de cinemática paralela” tiene como objetivo principal la implementación de un sistema de control que nos permita manejar un manipulador de cinemática paralela de dos grados de libertad accionado mediante dos motores eléctricos de corriente continua. Como componente central de este sistema de control, se dispondrá de un ordenador portátil cuyo procesador será el encargado de ejecutar las acciones necesarias para que pueda llevarse a cabo esta actividad de control. De esta forma, la tarea más importante y laboriosa a llevar cabo en este proyecto será el desarrollo de un aplicación de control que, corriendo en el citado ordenador, permitirá al usuario manejar el manipulador de cinemática paralela en cuestión. Para ello, esta aplicación deberá ser capaz de interpretar las ordenes de movimiento dadas por el usuario y transmitirlas al procesador del mencionado ordenador. Además de todo lo anterior, para completar el desarrollo del sistema de control, será necesaria la implementación de diversos sensores que se encargarán de detectar y transmitir las señales necesarias para evitar situaciones de emergencia en el que el manipulador estuviese a punto de chocar con algún objeto o persona. En conclusión, mediante el cumplimiento de los objetivos de este Trabajo de Fin de Grado, se va a disponer de un sistema de control sencillo, intuitivo y fácilmente operable, que va a permitir a cualquier futuro usuario del mismo el manejo de un robot de cinemática paralela.

The oculomotor system: (1) Vertical-horizontal interaction and signal recognition, (2) Time delays and power spectra

In the first section of this thesis, two-dimensional properties of the human eye movement control system were studied. The vertical - horizontal interaction was investigated by using a two-dimensional target motion consisting of a sinusoid in one of the directions vertical or horizontal, and low-pass filtered Gaussian random motion of variable bandwidth (and hence information content) in the orthogonal direction. It was found that the random motion reduced the efficiency of the sinusoidal tracking. However, the sinusoidal tracking was only slightly dependent on the bandwidth of the random motion. Thus the system should be thought of as consisting of two independent channels with a small amount of mutual cross-talk.

These target motions were then rotated to discover whether or not the system is capable of recognizing the two-component nature of the target motion. That is, the sinusoid was presented along an oblique line (neither vertical nor horizontal) with the random motion orthogonal to it. The system did not simply track the vertical and horizontal components of motion, but rotated its frame of reference so that its two tracking channels coincided with the directions of the two target motion components. This recognition occurred even when the two orthogonal motions were both random, but with different bandwidths.

In the second section, time delays, prediction and power spectra were examined. Time delays were calculated in response to various periodic signals, various bandwidths of narrow-band Gaussian random motions and sinusoids. It was demonstrated that prediction occurred only when the target motion was periodic, and only if the harmonic content was such that the signal was sufficiently narrow-band. It appears as if general periodic motions are split into predictive and non-predictive components.

For unpredictable motions, the relationship between the time delay and the average speed of the retinal image was linear. Based on this I proposed a model explaining the time delays for both random and periodic motions. My experiments did not prove that the system is sampled data, or that it is continuous. However, the model can be interpreted as representative of a sample data system whose sample interval is a function of the target motion.

It was shown that increasing the bandwidth of the low-pass filtered Gaussian random motion resulted in an increase of the eye movement bandwidth. Some properties of the eyeball-muscle dynamics and the extraocular muscle "active state tension" were derived.

Estimação de velocidade de composições usando processamento de vídeo

Esta dissertação tem como objetivo estudar um método para estimar a velocidade de veículos ferroviários usando processamento de vídeo. O sistema proposto consiste na utilização de câmeras ao longo das vias férreas que permitam não só o monitoramento do tráfego ferroviário, mas cujo vídeo captado possa ser utilizado para a obtenção de estimativas para a velocidade instantânea dos trens que por ela trafegam. Tal sistema seria utilizado independentemente dos sistemas de controle já utilizados pela operadora do sistema ferroviário, permitindo que os controladores possam ter uma segunda análise no caso de falha da primeira, assim como um modelo que permita avaliar a velocidade instantânea do veículo ferroviário ao longo do percurso. Os algoritmos de rastreamento empregados para esse fim abordaram diferentes métodos. Confrontaram-se os resultados obtidos com os algoritmos propostos com os dados empíricos de forma a determinar aquele com melhor resposta dada as características do sistema. O algoritmo que apresentou os melhores resultados emprega um único bloco de referência para todos os quadros comparados. A métrica de similaridade responsável por determinar quais blocos são mais ou menos similares dentro do universo de busca estipulado é a soma de diferenças absolutas (SAD, Sum of Absolute Differences). O tempo de processamento requerido por cada um dos métodos de rastreamento estudados também foi considerado nas avaliações de resultados apresentadas. Uma comparação realizada entre as velocidades coletadas e aquelas informadas pelo sistema de controle mostraram que os resultados obtidos com o sistema atual, utilizando a sinalização apenas por circuito de via apresenta resultados pouco confiáveis com erros bastante significativos. Os resultados obtidos com o sistema proposto apresentaram erros menores quando comparados àqueles obtidos pelo sistema vigente, apresentando-se assim como uma solução viável e de baixo custo quando comparada às técnicas atualmente empregadas para a medida de velocidade de trens.

A Data Dropout Compensation Algorithm Based on the Iterative Learning Control Methodology for Discrete-Time Systems

This paper deals with the convergence of a remote iterative learning control system subject to data dropouts. The system is composed by a set of discrete-time multiple input-multiple output linear models, each one with its corresponding actuator device and its sensor. Each actuator applies the input signals vector to its corresponding model at the sampling instants and the sensor measures the output signals vector. The iterative learning law is processed in a controller located far away of the models so the control signals vector has to be transmitted from the controller to the actuators through transmission channels. Such a law uses the measurements of each model to generate the input vector to be applied to its subsequent model so the measurements of the models have to be transmitted from the sensors to the controller. All transmissions are subject to failures which are described as a binary sequence taking value 1 or 0. A compensation dropout technique is used to replace the lost data in the transmission processes. The convergence to zero of the errors between the output signals vector and a reference one is achieved as the number of models tends to infinity.

Robust Sliding Control of SEIR Epidemic Models

This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. Initially, the controller is designed assuming certain knowledge of an upper-bound of the uncertainty signal. Afterwards, this condition is removed while an adaptive sliding control system is designed. The closed-loop properties are proved mathematically in the nonadaptive and adaptive cases. Furthermore, the usual sign function appearing in the sliding-mode control is substituted by the saturation function in order to prevent chattering. In addition, the properties achieved by the closed-loop system under this variation are also stated and proved analytically. The closed-loop system is able to attain the control objective regardless of the parametric uncertainties of the model and the lack of a priori knowledge on the system.

Computational approaches to motor control.

This review will focus on four areas of motor control which have recently been enriched both by neural network and control system models: motor planning, motor prediction, state estimation and motor learning. We will review the computational foundations of each of these concepts and present specific models which have been tested by psychophysical experiments. We will cover the topics of optimal control for motor planning, forward models for motor prediction, observer models of state estimation arid modular decomposition in motor learning. The aim of this review is to demonstrate how computational approaches, as well as proposing specific models, provide a theoretical framework to formalize the issues in motor control.

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

Some biocybernetic aspects in gene expression and regulatory control

In eucaryotes, gene expression and control is a complex nonlinear process, where there are many control mechanisms and ways, both physic, chemical and informational control. By the exploration from the angle of biocybernetics, the authors suggest that gene expression is a co-control process. In this process, physic, chemical and informational feedback controls are associated and influential each other, and are cross and co-functional. The physic, chemical and informational control ways composed an order non-linear feedback control system in eucaryotes.