Estudio y diseño de filtros pasobanda y en banda dual basados en resonadores microstrip open-loop acoplados

El proyecto está dedicado al estudio y diseño de filtros paso-banda y en banda dual con tecnología microstrip mediante estructuras resonantes de tipo open-loop. Se ha llevado a cabo el diseño de un filtro paso-banda con respuesta Chebyshev, un filtro pasobanda con ceros de transmisión y un filtro de banda dual para WCDMA y WiFi, empleado el método de diseño para filtros basados en resonadores inter-acoplados. Se presentan los modelos eléctricos de los filtros de RF simulados junto con sus respectivos layouts y se comparan las respuestas obtenidas de los dispositivos con las respuestas ideales. En el proyecto se realiza un estudio del comportamiento de los diferentes tipos de acoplamiento entre resonadores open-loop en función de la geometría de la estructura. Las tendencias de comportamiento de los acoplamientos permiten el diseño y colocación de los resonadores para satisfacer las especificaciones del filtro.

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Dynamic diagnosis based on interval analytical redundancy relations and signs of the symptoms

A model-based approach for fault diagnosis is proposed, where the fault detection is based on checking the consistencyof the Analytical Redundancy Relations (ARRs) using an interval tool. The tool takes into account the uncertainty in theparameters and the measurements using intervals. Faults are explicitly included in the model, which allows for the exploitation of additional information. This information is obtained from partial derivatives computed from the ARRs. The signs in the residuals are used to prune the candidate space when performing the fault diagnosis task. The method is illustrated using a two-tank example, in which these aspects are shown to have an impact on the diagnosis and fault discrimination, since the proposed method goes beyond the structural methods

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented