Stability analysis of RF amplifiers based on MIMO pole-zero identification

Spurious oscillations are one of the principal issues faced by microwave and RF circuit designers. The rigorous detection of instabilities or the characterization of measured spurious oscillations is still an ongoing challenge. This project aims to create a new stability analysis CAD program that tackles this chal- lenge. Multiple Input Multiple Output (MIMO) pole-zero identification analysis is introduced on the program as a way to create new methods to automate the stability analysis process and to help designers comprehend the obtained results and prevent incorrect interpretations. The MIMO nature of the analysis contributes to eliminate possible controllability and observability losses and helps differentiate mathematical and physical quasi-cancellations, products of overmodeling. The created program reads Single Input Single Output (SISO) or MIMO frequency response data, and determines the corresponding continuous transfer functions with Vector Fitting. Once the transfer function is calculated, the corresponding pole/zero diagram is mapped enabling the designers to analyze the stability of an amplifier. Three data processing methods are introduced, two of which consist of pole/zero elimina- tions and the latter one on determining the critical nodes of an amplifier. The first pole/zero elimination method is based on eliminating non resonant poles, whilst the second method eliminates the poles with small residue by assuming that their effect on the dynamics of a system is small or non-existent. The critical node detection is also based on the residues; the node at which the effect of a pole on the dynamics is highest is defined as the critical node. In order to evaluate and check the efficiency of the created program, it is compared via examples with another existing commercial stability analysis tool (STAN tool). In this report, the newly created tool is proved to be as rigorous as STAN for detecting instabilities. Additionally, it is determined that the MIMO analysis is a very profitable addition to stability analysis, since it helps to eliminate possible problems of loss of controllability, observability and overmodeling.

Interacción y programación de trayectorias de robot industrial tipo SCARA.

[ES]En el desarrollo de este Trabajo de Fin De Grado (TFG) en el curso 2014-2015 se ha trabajado con un robot de tipo SCARA, muy utilizado en la industria. El objetivo era analizar su cinemática y programar trayectorias que el robot pudiera realizar. En primer lugar se ha llevado a cabo un estudio del Estado del Arte, en el que se describe la robótica industrial y su desarrollo histórico hasta nuestros días, desarrollo que presenta un futuro prometedor. Además, se han descrito las particularidades que atañen al SCARA: sus características, su relevancia y su historia. En cuanto al robot, previamente se ha realizado un análisis cinemático del SCARA. Mediante métodos matriciales se han resuelto los problemas de posiciones y velocidades, para luego programarlas en MATLAB. Una vez comprendida su cinemática, se ha interactuado con él en el taller para poder entender su funcionamiento, sus componentes y su control. Después, con los conocimientos que se han adquirido, se han programado varias trayectorias usando el lenguaje del robot, el lenguaje V+, para finalmente ejecutar esos movimientos. El Trabajo se completa con la descripción de las tareas mediante un diagrama de Gantt, el presupuesto, la declaración de gastos y el análisis de riesgos.

Analysis and Use of Information and Communication Tools in Economics of Climate Change

16 p.

Modeling the Links between Biodiversity, Ecosystem Services and Human Wellbeing in the Context of Climate Change: Results from an Econometric Analysis on the European Forest Ecosystems

25 p.

Regional IAM: analysis of risk-adjusted costs and benefits of climate policies

23 p.

Local air pollution and global climate change taxes: a distributional analysis

25 p.

Analysis of multivariate stochastic signals sampled by on-line particle analyzers: Application to the quantitative assessment of occupational exposure to NOAA in multisource industrial scenarios (MSIS)

In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed

Assessment of faculty training program for the use of e-learning platforms: analysis of current use

5th International Conference on Education and New Learning Technologies (Barcelona, Spain. 1-3 July, 2013)