Frequency Domain Approaches to Fault Detection in Closed-Loop Systems

This thesis describes fault detection techniques which can be applied to closed-loop automatic control systems. Particular emphasis is placed upon frequency domain methods. Digital simulation is used for the evaluation of on-line techniques for fault detection using pseudo-random-binary test signals. This simulation work involves a simple process model based on a two tank liquid flow control system. Frequency-domain identification using pseudo-random-binary test signals is performed by means of a mixed radix-2 fast Fourier transformation technique. This technique avoids the synchronisation problems which arise when the more conventional radix-2 transformation is used with pseudo-random binary test signals. A novel method of parameter sensitivity analysis is investigated both in terms of the identification of faults and for system optimisation following fault occurrence

Nonparametric Estimation in Random Coefficients Binary Choice Models

This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed, utilizing Fourier-Laplace series on spheres. This approach offers a clear insight on the identification problem. More importantly, it leads to a closed form estimator formula that yields a simple plug-in procedure requiring no numerical optimization. The new estimator, therefore, is easy to implement in empirical applications, while being flexible about the treatment of unobserved heterogeneity. Extensions including treatments of non-random coefficients and models with endogeneity are discussed.Inverse problems, Discrete choice models

Identification of binary cellular automata from spatiotemporal binary patterns using a fourier representation

The identification of binary cellular automata from spatio-temporal binary patterns is investigated in this paper. Instead of using the usual Boolean or multilinear polynomial representation, the Fourier transform representation of Boolean functions is employed in terms of a Fourier basis. In this way, the orthogonal forward regression least-squares algorithm can be applied directly to detect the significant terms and to estimate the associated parameters. Compared with conventional methods, the new approach is much more robust to noise. Examples are provided to illustrate the effectiveness of the proposed approach

The VLTI / PIONIER near-infrared interferometric survey of southern T Tauri stars. I. First results

Context : The properties of the inner disks of bright Herbig AeBe stars have been studied with near infrared (NIR) interferometry and high resolution spectroscopy. The continuum and a few molecular gas species have been studied close to the central star; however, sensitivity problems limit direct information about the inner disks of the fainter T Tauri stars. Aims : Our aim is to measure some of the properties of the inner regions of disks surrounding southern T Tauri stars. Methods : We performed a survey with the PIONIER recombiner instrument at H-band of 21 T Tauri stars. The baselines used ranged from 11 m to 129 m, corresponding to a maximum resolution of 3mas (0.45 au at 150 pc). Results : Thirteen disks are resolved well and the visibility curves are fully sampled as a function of baseline in the range 45-130 m for these 13 objects. A simple qualitative examination of visibility profiles allows us to identify a rapid drop-off in the visibilities at short baselines in 8 resolved disks. This is indicative of a significant contribution from an extended contribution of light from the disk. We demonstrate that this component is compatible with scattered light, providing strong support to a prediction made by Pinte et al. (2008). The amplitude of the drop-off and the amount of dust thermal emission changes from source to source suggesting that each disk is different. A by-product of the survey is the identification of a new milli-arcsec separation binary: WW Cha. Spectroscopic and interferometric data of AK Sco have also been fitted with a binary and disk model. Conclusions : Visibility data are reproduced well when thermal emission and scattering form dust are fully considered. The inner radii measured are consistent with the expected dust sublimation radii. Modelling of AK Sco suggests a likely coplanarity between the disk and the binary's orbital planeComment: 19 pages, 11 figure

Perfect tag identification protocol in RFID networks

Radio Frequency IDentification (RFID) systems are becoming more and more popular in the field of ubiquitous computing, in particular for objects identification. An RFID system is composed by one or more readers and a number of tags. One of the main issues in an RFID network is the fast and reliable identification of all tags in the reader range. The reader issues some queries, and tags properly answer. Then, the reader must identify the tags from such answers. This is crucial for most applications. Since the transmission medium is shared, the typical problem to be faced is a MAC-like one, i.e. to avoid or limit the number of tags transmission collisions. We propose a protocol which, under some assumptions about transmission techniques, always achieves a 100% perfomance. It is based on a proper recursive splitting of the concurrent tags sets, until all tags have been identified. The other approaches present in literature have performances of about 42% in the average at most. The counterpart is a more sophisticated hardware to be deployed in the manufacture of low cost tags.Comment: 12 pages, 1 figur

Input Design for System Identification via Convex Relaxation

This paper proposes a new framework for the optimization of excitation inputs for system identification. The optimization problem considered is to maximize a reduced Fisher information matrix in any of the classical D-, E-, or A-optimal senses. In contrast to the majority of published work on this topic, we consider the problem in the time domain and subject to constraints on the amplitude of the input signal. This optimization problem is nonconvex. The main result of the paper is a convex relaxation that gives an upper bound accurate to within $2/\pi$ of the true maximum. A randomized algorithm is presented for finding a feasible solution which, in a certain sense is expected to be at least $2/\pi$ as informative as the globally optimal input signal. In the case of a single constraint on input power, the proposed approach recovers the true global optimum exactly. Extensions to situations with both power and amplitude constraints on both inputs and outputs are given. A simple simulation example illustrates the technique.Comment: Preprint submitted for journal publication, extended version of a paper at 2010 IEEE Conference on Decision and Contro