Unidad de efectos de audio en Simulink

La tecnología moderna de computación ha permitido cambiar radicalmente la investigación tecnológica en todos los ámbitos. El proceso general utilizado previamente consistía en el desarrollo de prototipos analógicos, creando múltiples versiones del mismo hasta llegar al resultado adecuado. Este es un proceso costoso a nivel económico y de carga de trabajo. Es por ello por lo que el proceso de investigación actual aprovecha las nuevas tecnologías para lograr el objetivo final mediante la simulación. Gracias al desarrollo de software para la simulación de distintas áreas se ha incrementado el ritmo de crecimiento de los avances tecnológicos y reducido el coste de los proyectos en investigación y desarrollo. La simulación, por tanto, permite desarrollar previamente prototipos simulados con un coste mucho menor para así lograr un producto final, el cual será llevado a cabo en su ámbito correspondiente. Este proceso no sólo se aplica en el caso de productos con circuitería, si bien es utilizado también en productos programados. Muchos de los programas actuales trabajan con algoritmos concretos cuyo funcionamiento debe ser comprobado previamente, para después centrarse en la codificación del mismo. Es en este punto donde se encuentra el objetivo de este proyecto, simular algoritmos de procesado digital de la señal antes de la codificación del programa final. Los sistemas de audio están basados en su totalidad en algoritmos de procesado de la señal, tanto analógicos como digitales, siendo estos últimos los que están sustituyendo al mundo analógico mediante los procesadores y los ordenadores. Estos algoritmos son la parte más compleja del sistema, y es la creación de nuevos algoritmos la base para lograr sistemas de audio novedosos y funcionales. Se debe destacar que los grupos de desarrollo de sistemas de audio presentan un amplio número de miembros con cometidos diferentes, separando las funciones de programadores e ingenieros de la señal de audio. Es por ello por lo que la simulación de estos algoritmos es fundamental a la hora de desarrollar nuevos y más potentes sistemas de audio. Matlab es una de las herramientas fundamentales para la simulación por ordenador, la cual presenta utilidades para desarrollar proyectos en distintos ámbitos. Sin embargo, en creciente uso actualmente se encuentra el software Simulink, herramienta especializada en la simulación de alto nivel que simplifica la dificultad de la programación en Matlab y permite desarrollar modelos de forma más rápida. Simulink presenta una completa funcionalidad para el desarrollo de algoritmos de procesado digital de audio. Por ello, el objetivo de este proyecto es el estudio de las capacidades de Simulink para generar sistemas de audio funcionales. A su vez, este proyecto pretende profundizar en los métodos de procesado digital de la señal de audio, logrando al final un paquete de sistemas de audio compatible con los programas de edición de audio actuales. ABSTRACT. Modern computer technology has dramatically changed the technological research in multiple areas. The overall process previously used consisted of the development of analog prototypes, creating multiple versions to reach the proper result. This is an expensive process in terms of an economically level and workload. For this reason actual investigation process take advantage of the new technologies to achieve the final objective through simulation. Thanks to the software development for simulation in different areas the growth rate of technological progress has been increased and the cost of research and development projects has been decreased. Hence, simulation allows previously the development of simulated protoypes with a much lower cost to obtain a final product, which will be held in its respective field. This process is not only applied in the case of circuitry products, but is also used in programmed products. Many current programs work with specific algorithms whose performance should be tested beforehand, which allows focusing on the codification of the program. This is the main point of this project, to simulate digital signal processing algorithms before the codification of the final program. Audio systems are entirely based on signal processing, both analog and digital systems, being the digital systems which are replacing the analog world thanks to the processors and computers. This algorithms are the most complex part of every system, and the creation of new algorithms is the most important step to achieve innovative and functional new audio systems. It should be noted that development groups of audio systems have a large number of members with different roles, separating them into programmers and audio signal engineers. For this reason, the simulation of this algorithms is essential when developing new and more powerful audio systems. Matlab is one of the most important tools for computer simulation, which has utilities to develop projects in different areas. However, the use of the Simulink software is constantly growing. It is a simulation tool specialized in high-level simulations which simplifies the difficulty of programming in Matlab and allows the developing of models faster. Simulink presents a full functionality for the development of algorithms for digital audio processing. Therefore, the objective of this project is to study the posibilities of Simulink to generate funcional audio systems. In turn, this projects aims to get deeper into the methods of digital audio signal processing, making at the end a software package of audio systems compatible with the current audio editing software.

Un nuovo modello computazionale di fibra di Purkinje umana: dal modello medio alla popolazione di modelli e ritorno.

Il lavoro presentato in questa tesi è stato svolto presso il Department of Computer Science, University of Oxford, durante il mio periodo all’estero nel Computational Biology Group. Scopo del presente lavoro è stato lo sviluppo di un modello matematico del potenziale d’azione per cellule umane cardiache di Purkinje. Tali cellule appartengono al sistema di conduzione elettrico del cuore, e sono considerate molto importanti nella genesi di aritmie. Il modello, elaborato in linguaggio Matlab, è stato progettato utilizzando la tecnica delle Popolazione di Modelli, un innovativo approccio alla modellazione cellulare sviluppato recentemente proprio dal Computational Biology Group. Tale modello è stato sviluppato in 3 fasi: • Inizialmente è stato sviluppato un nuovo modello matematico di cellula umana del Purkinje cardiaco, tenendo in considerazione i modelli precedenti disponibili in letteratura e le più recenti pubblicazioni in merito alle caratteristiche elettrofisiologiche proprie della cellula cardiaca umana di Purkinje. Tale modello è stato costruito a partire dall’attuale gold standard della modellazione cardiaca ventricolare umana, il modello pubblicato da T. O’Hara e Y. Rudy nel 2011, modificandone sia le specifiche correnti ioniche che la struttura interna cellulare. • Il modello così progettato è stato, poi, utilizzato come “modello di base” per la costruzione di una popolazione di 3000 modelli, tramite la variazione di alcuni parametri del modello all’interno di uno specifico range. La popolazione così generata è stata calibrata sui dati sperimentali di cellule umane del Purkinje. A valle del processo di calibrazione si è ottenuta una popolazione di 76 modelli. • A partire dalla popolazione rimanente, è stato ricavato un nuovo modello ai valori medi, che riproduce le principali caratteristiche del potenziale d’azione di una cellula di Purkinje cardiaca umana, e che rappresenta il dataset sperimentale utilizzato nel processo di calibrazione.

Modellistica e controllo di attuatori idraulici

La tesi tratta della modellistica e del controllo di un attuatore idraulico con valvola a quattro vie. Inizialmente si definiscono le grandezze e le formule fondamentali per descrivere un sistema idraulico e costruirne il modello matematico. Successivamente si ricava il modello non lineare del sistema nello spazio degli stati, quindi lo si linearizza per poterlo descrivere e studiare anche tramite funzioni di trasferimento. Si ricava quindi, utilizzando anche Matlab e Simulink, il controllo da applicare al modello linearizzato e si testa il comportamento del sistema in risposta a diversi segnali di ingresso. Infine si applica lo stesso controllore al sistema non lineare e si confrontano i due diversi comportamenti.

Analisi e simulazione di un ciclo Rankine organico per il recupero di energia a bassa entalpia.

Questo lavoro è incentrato sull'analisi e la simulazione di un ciclo Rankine a fluido organico (ORC) per la produzione di energia da calore a bassa entalpia. Il lavoro è stato svolto in collaborazione con l'università di Gent, in Belgio, in particolare grazie al Prof. De Peape e all' Ing. Steven Lecompte; il lavoro in Italia è stato coordinato dal Prof. De Pascale. L'obiettivo principale della tesi è stata la creazione un modello computazionale in grado di descrivere le prestazioni dell'impianto a carico parziale. Ogni elemento dell'impianto è stato analizzato e modellizzato secondo un approccio di simulazione originale in Matlab. I componenti ottenuti sono stati poi combinati a formare la simulazione dell'intero sistema; questa è in grado di prevedere la potenza prodotta ed il rendimento del ciclo al variare delle condizioni esterne. I risultati ottenuti dalle simulazioni sono stati poi confrontati con i dati sperimentali raccolti sull'impianto di prova dell'Università. Questo confronto dimostra un buon accordo dei risultati previsti con quelli misurati. L'errore relativo massimo ottenuto per la potenza elettrica è sotto il 7%, così come quello sul rendimento; Gli errori relativi a pressione ed entalpie sono in genere sotto il 5%. Il modello può perciò dirsi validato e rappresenta un valido strumento di analisi per comprendere la risposta ai carichi parziali anche al di fuori del range di calibrazione. Il modello è stato infine utilizzato per costruire delle mappe del carico parziale e analizzare l'influenza delle variabili del ciclo. Ulteriori applicazioni delle mappe prodotte sono proposte a fine del lavoro.

MATLAB toolboxes : robotics and vision for students and teachers

In this column, Dr. Peter Corke of CSIRO, Australia, gives us a description of MATLAB Toolboxes he has developed. He has been passionately developing tools to enable students and teachers to better understand the theoretical concepts behind classical robotics and computer vision through easy and intuitive simulation and visualization. The results of this labor of love have been packaged as MATLAB Toolboxes: the Robotics Toolbox and the Vision Toolbox. –Daniela Rus, RAS Education Cochair

The Machine Vision Toolbox : A MATLAB Toolbox for vision and vision-based control

The article described an open-source toolbox for machine vision called Machine Vision Toolbox (MVT). MVT includes more than 60 functions including image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration, and color space conversion. MVT can be used for research into machine vision but is also versatile enough to be usable for real-time work and even control. MVT, combined with MATLAB and a model workstation computer, is a useful and convenient environment for the investigation of machine vision algorithms. The article illustrated the use of a subset of toolbox functions for some typical problems and described MVT operations including the simulation of a complete image-based visual servo system.

Development of a software model of a heavy vehicle suspension for research

A Simulink Matlab control system of a heavy vehicle suspension has been developed. The aim of the exercise presented in this paper was to develop a Simulink Matlab control system of a heavy vehicle suspension. The objective facilitated by this outcome was the use of a working model of a heavy vehicle (HV) suspension that could be used for future research. A working computer model is easier and cheaper to re-configure than a HV axle group installed on a truck; it presents less risk should something go wrong and allows more scope for variation and sensitivity analysis before embarking on further "real-world" testing. Empirical data recorded as the input and output signals of a heavy vehicle (HV) suspension were used to develop the parameters for computer simulation of a linear time invariant system described by a second-order differential equation of the form: (i.e. a "2nd-order" system). Using the empirical data as an input to the computer model allowed validation of its output compared with the empirical data. The errors ranged from less than 1% to approximately 3% for any parameter, when comparing like-for-like inputs and outputs. The model is presented along with the results of the validation. This model will be used in future research in the QUT/Main Roads project Heavy vehicle suspensions – testing and analysis, particularly so for a theoretical model of a multi-axle HV suspension with varying values of dynamic load sharing. Allowance will need to be made for the errors noted when using the computer models in this future work.

Machine vision toolbox for MATLAB, release 3 [Software]

The Toolbox, combined with MATLAB ® and a modern workstation computer, is a useful and convenient environment for investigation of machine vision algorithms. For modest image sizes the processing rate can be sufficiently ``real-time'' to allow for closed-loop control. Focus of attention methods such as dynamic windowing (not provided) can be used to increase the processing rate. With input from a firewire or web camera (support provided) and output to a robot (not provided) it would be possible to implement a visual servo system entirely in MATLAB. Provides many functions that are useful in machine vision and vision-based control. Useful for photometry, photogrammetry, colorimetry. It includes over 100 functions spanning operations such as image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration and color space conversion.

A novel CDVM based high-voltage converter using low power solid-state switches and a tuned resonant circuit designed for pulsed power applications

A novel concept of producing high dc voltage for pulsed-power applications is proposed in this paper. The topology consists of an LC resonant circuit supplied through a tuned alternating waveform that is produced by an inverter. The control scheme is based on the detection of variations in the resonant frequency and adjustment of the switching signal patterns for the inverter to produce a square waveform with exactly the same frequencies. Therefore the capacitor voltage oscillates divergently with an increasing amplitude. A simple one-stage capacitor-diode voltage multiplier (CDVM) connected to the resonant capacitor then rectifies the alternating voltage and gives a dc level equal to twice the input voltage amplitude. The produced high voltage appears then in the form of high-voltage pulses across the load. A basic model is simulated by Simulink platform of MATLAB and the results are included in the paper.

Evaluating MPPT converter topologies using a Matlab PV model

An accurate PV module electrical model is presented based on the Shockley diode equation. The simple model has a photo-current current source, a single diode junction and a series resistance, and includes temperature dependences. The method of parameter extraction and model evaluation in Matlab is demonstrated for a typical 60W solar panel. This model is used to investigate the variation of maximum power point with temperature and isolation levels. A comparison of buck versus boost maximum power point tracker (MPPT) topologies is made, and compared with a direct connection to a constant voltage (battery) load. The boost converter is shown to have a slight advantage over the buck, since it can always track the maximum power point.

Evaluating MPPT converter topologies using a MATLAB PV model

An accurate PV module electrical model is presented based on the Shockley diode equation. The simple model has a photo-current current source, a single diode junction and a series resistance, and includes temperature dependences. The method of parameter extraction and model evaluation in Matlab is demonstrated for a typical 60W solar panel. This model is used to investigate the variation of maximumpower point with temperature and insolation levels. A comparison of buck versus boostmaximum power point tracker (MPPT) topologies is made, and compared with a direct connection to a constant voltage (battery) load. The boost converter is shown to have a slight advantage over the buck, since it can always track the maximum power point.

A Matlab toolbox for parametric identification of radiation-force models of ships and offshore structures

This article describes a Matlab toolbox for parametric identification of fluid-memory models associated with the radiation forces ships and offshore structures. Radiation forces are a key component of force-to-motion models used in simulators, motion control designs, and also for initial performance evaluation of wave-energy converters. The software described provides tools for preparing non-parmatric data and for identification with automatic model-order detection. The identification problem is considered in the frequency domain.

Bond graph toolbox for handling complex variable

Bond graph is an apt modelling tool for any system working across multiple energy domains. Power electronics system modelling is usually the study of the interplay of energy in the domains of electrical, mechanical, magnetic and thermal. The usefulness of bond graph modelling in power electronic field has been realised by researchers. Consequently in the last couple of decades, there has been a steadily increasing effort in developing simulation tools for bond graph modelling that are specially suited for power electronic study. For modelling rotating magnetic fields in electromagnetic machine models, a support for vector variables is essential. Unfortunately, all bond graph simulation tools presently provide support only for scalar variables. We propose an approach to provide complex variable and vector support to bond graph such that it will enable modelling of polyphase electromagnetic and spatial vector systems. We also introduced a rotary gyrator element and use it along with the switched junction for developing the complex/vector variable's toolbox. This approach is implemented by developing a complex S-function tool box in Simulink inside a MATLAB environment This choice has been made so as to synthesise the speed of S-function, the user friendliness of Simulink and the popularity of MATLAB.