Grey-box state-space identification of nonlinear mechanical vibrations

The present paper deals with the identification of nonlinear mechanical vibrations. A grey-box, or semi-physical, nonlinear state-space representation is introduced, expressing the nonlinear basis functions using a limited number of measured output variables. This representation assumes that the observed nonlinearities are localised in physical space, which is a generic case in mechanics. A two-step identification procedure is derived for the grey-box model parameters, integrating nonlinear subspace initialisation and weighted least-squares optimisation. The complete procedure is applied to an electrical circuit mimicking the behaviour of a single-input, single-output (SISO) nonlinear mechanical system and to a single-input, multiple-output (SIMO) geometrically nonlinear beam structure

Linear parameter-varying model to design control laws for an artificial pancreas

The contribution of this work is the generation of a control-oriented model for insulin-glucose dynamic regulation in type 1 diabetes mellitus (T1DM). The novelty of this model is that it includes the time-varying nature, and the inter-patient variability of the glucose-control problem. In addition, the model is well suited for well-known and standard controller synthesis procedures. The outcome is an average linear parameter-varying (LPV) model that captures the dynamics from the insulin delivery input to the glucose concentration output constructed based on the UVA/Padova metabolic simulator. Finally, a system-oriented reinterpretation of the classical ad-hoc 1800 rule is applied to adapt the model's gain. The effectiveness of this approach is quantified both in open- and closed-loop. The first one by computing the root mean square error (RMSE) between the glucose deviation predicted by the proposed model and the UVA/Padova one. The second measure is determined by using the ν-gap as a metric to determine distance, in terms of closed-loop performance, between both models. For comparison purposes, both open- (RMSE) and closed-loop (ν-gap metric) quality indicators are also computed for other control-oriented models previously presented. This model allows the design of LPV controllers in a straightforward way, considering its affine dependence on the time-varying parameter, which can be computed in real-time. Illustrative simulations are included. In addition, the presented modeling strategy was employed in the design of an artificial pancreas (AP) control law that successfully withstood rigorous testing using the UVA/Padova simulator, and that was subsequently deployed in a clinical trial campaign where five adults remained in closed-loop for 36 h. This was the first ever fully closed-loop clinical AP trial in Argentina, and the modeling strategy presented here is considered instrumental in resulting in a very successful clinical outcome.Fil: Colmegna, Patricio Hernán. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sánchez Peña, Ricardo S.. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gondhalekar, R.. Harvard University; Estados Unido

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification

A novel topographic parameterization scheme indicates that martian gullies display the signature of liquid water

Martian gullies resemble gullies carved by water on Earth, yet are thought to have formed in an extremely cold (2-driven processes. That this argument persists demonstrates the limitations of morphological interpretations made from 2D images, especially when similar-looking landforms can form by very different processes. To overcome this we have devised a parameterization scheme, based on statistical discriminant analysis and hydrological terrain analysis of meter-scale digital topography data, which can distinguish between dry and wet surface processes acting on a landscape. Applying this approach to new meter-scale topographic datasets of Earth, the Moon and Mars, we demonstrate that martian gullied slopes are dissimilar to dry, gullied slopes on Earth and the Moon, but are similar to both terrestrial debris flows and fluvial gullies. We conclude that liquid water was integral to the process by which martian gullies formed. Finally, our work shows that quantitative 3D analyses of landscape have great potential as a tool in planetary science, enabling remote assessment of processes acting on planetary surfaces

Enhanced tracking and recognition of moving objects by reasoning about spatio-temporal continuity.

A framework for the logical and statistical analysis and annotation of dynamic scenes containing occlusion and other uncertainties is presented. This framework consists of three elements; an object tracker module, an object recognition/classification module and a logical consistency, ambiguity and error reasoning engine. The principle behind the object tracker and object recognition modules is to reduce error by increasing ambiguity (by merging objects in close proximity and presenting multiple hypotheses). The reasoning engine deals with error, ambiguity and occlusion in a unified framework to produce a hypothesis that satisfies fundamental constraints on the spatio-temporal continuity of objects. Our algorithm finds a globally consistent model of an extended video sequence that is maximally supported by a voting function based on the output of a statistical classifier. The system results in an annotation that is significantly more accurate than what would be obtained by frame-by-frame evaluation of the classifier output. The framework has been implemented and applied successfully to the analysis of team sports with a single camera. Key words: Visua

Asteroseismology with the WIRE satellite. I. Combining Ground- and Space-based Photometry of the Delta Scuti Star Epsilon Cephei

We have analysed ground-based multi-colour Stromgren photometry and single-filter photometry from the star tracker on the WIRE satellite of the delta scuti star Epsilon Cephei. The ground-based data set consists of 16 nights of data collected over 164 days, while the satellite data are nearly continuous coverage of the star during 14 days. The spectral window and noise level of the satellite data are superior to the ground-based data and this data set is used to locate the frequencies. However, we can use the ground-based data to improve the accuracy of the frequencies due to the much longer time baseline. We detect 26 oscillation frequencies in the WIRE data set, but only some of these can be seen clearly in the ground-based data. We have used the multi-colour ground-based photometry to determine amplitude and phase differences in the Stromgren b-y colour and the y filter in an attempt to identify the radial degree of the oscillation frequencies. We conclude that the accuracies of the amplitudes and phases are not sufficient to constrain theoretical models of Epsilon Cephei. We find no evidence for rotational splitting or the large separation among the frequencies detected in the WIRE data set. To be able to identify oscillation frequencies in delta scuti stars with the method we have applied, it is crucial to obtain more complete coverage from multi-site campaigns with a long time baseline and in multiple filters. This is important when planning photometric and spectroscopic ground-based support for future satellite missions like COROT and KEPLER.Comment: 13 pages, 12 figures, 4 tables. Fig. 4 reduced in quality. Accepted by A&