1,721,038 research outputs found
Dwell-time controllers for stochastic systems with switching Markov chain
No full textWe study the problem of feedback stabilization of a family of nonlinear stochastic systems with switching mechanism modeled by a Markov chain. We introduce a novel notion of stability under switching, which guarantees a given probability that the trajectories of the system hit some target set in finite time and remain thereinafter. Our main contribution is to prove that if the expectation of the time between two consecutive switching (dwell time) is "sufficiently large", then the system is stable under switching with guaranteed probability. We, illustrate this methodology by constructing measurement feedback controllers for a wide class of stochastic nonlinear systems. (c) 2005 Elsevier Ltd. All rights reserved
Discrete level set segmentation for pupil morphology characterization
No full textThe pupil morphological characteristics are of great interest for non invasive early diagnosis of the central nervous system response to environmental stimuli of different nature. Their evaluation in subjects suffering some typical diseases such as diabetes, Alzheimer disease, schizophrenia, drug and alcohol addiction is of concern. In this paper geometrical pupil features such as area, centroid coordinates, eccentricity, major and minor axes lengths are estimated by a procedure based on an image segmentation algorithm. It exploits the level set formulation of the related variational problem. A discrete set up of this problem is proposed: an arbitrary initial curve is evolved towards the unique optimal segmentation boundary by a difference equation. Numerical tests are performed on real pupillometry data taken in different illumination conditions showing a high degree of robustness of the shape parameters estimates
Stabilization and control of a flexible structure continuum model
No full textIn this paper the stabilization problem for a flexible slewing link is considered, leading to some interesting considerations about the use of positive real compensators. By modelling the structure motion as a set of first order differential equations on a proper Hilbert space, the authors study this problem in an infinite-dimensional setting by following two approaches. In the first one standard results on semigroups theory are considered, while in the second the authors use passivity arguments, directly related to the classical Lyapunov direct method. Control applications such as set-point motion and LQR are finally reviewe
A region growing method for medical images segmentation
No full textDiagnosis by medical images implies the expert ability of recognizing patterns of interest in terms of some features like gray (or color) level intensity, shape attributes, texture. The image segmentation algorithms constitute a valid support in the analysis of medical images by providing reliable computer tools able to separate the objects of interest from the background. There is a great deal of segmentation algorithms depending on the mathematical model adopted for the information to be retrieved from data. They span from very simple and fast threshold procedures, to local signal processing like edge detection, to sophisticated ones based on global optimization methods. This work describes a region growing algorithm that falls within the last framework; it is based on a novel image model. It is formulated in the discrete domain to deal directly with the image data without approximation schemes required by the formulation in the continuum domain, typical of the variational methods. The segmentation procedure is efficient and reliable, allowing a hierarchical processing also in term of the signal components. It can easily take into account a wide range of situations occurring in the medical environment, going from the analysis of angiographies to the analysis of CT scan images of human body organs. © 2010 by IJTS, ISDER
Stabilization in probability of nonlinear stochastic systems with guaranteed cost
No full textWe deal with nonlinear dynamical systems, consisting of a linear nominal part plus model uncertainties, nonlinearities, and both additive and multiplicative random noise, modeled as a Wiener process. In particular, we study the problem of finding suitable measurement feedback control laws such that the resulting closed-loop system is stable in some probabilistic sense and a given cost functional is minimized. We give a Lyapunov-based separation result which splits the control design into a state feedback problem and a filtering problem. Finally, we point out constructive algorithms for solving the state feedback and filtering problems with arbitrarily large region of attraction for a wide class of nonlinear systems, which at least include feedback linearizable systems
Robust output feedback control of nonlinear systems using neural networks
No full textWe present an adaptive output feedback controller for a class of uncertain stochastic nonlinear systems. The plant dynamics is represented as a nominal linear system plus nonlinearities. In turn, these nonlinearities are decomposed into a part, obtained as the best approximation given by neural networks, plus a remaining part which is treated as uncertainties, modeling approximation errors, and neglected dynamics. The weights of the neural network are tuned adaptively by a Lyapunov design. The proposed controller is obtained through robust optimal design and combines together parameter projection, control saturation, and high-gain observers. High performances are obtained in terms of large errors tolerance as shown through simulations
Video sequences analysis for eye tracking
No full textAn efficient eye tracking procedure is presented providing a non-invasive method for real time detection of a subject eyes in a sequence of frames captured by low cost equipment. The procedure can be easily adapted to any subject and is adequately insensitive to the illumination changes. The eye identification is performed by an optimal approximation procedure of the frames based on a discrete level set formulation of the variational approach to the optimal segmentation problem. The segmentation yields a simplified version of the original data retaining all the information relevant to the application. No eye movement model is required being the procedure fast enough to obtain the current frame segmentation as one step update from the previous frame segmentation
Robust real time eye tracking for computer interface for disabled people
No full textGaze is a natural input for a Human Computer Interface (HCI) for disabled people, who have of course an acute need for a communication system. An efficient eye tracking procedure is presented providing a non-invasive method for real time detection of a subject eyes in a sequence of frames captured by low cost equipment. The procedure can be easily adapted to any subject and is adequately insensitive to changing of the illumination. The eye identification is performed on a piece-wise constant approximation of the frames. it is based on a discrete level set formulation of the variational approach to the optimal segmentation problem. This yields a simplified version of the original data retaining all the information relevant to the application. Tracking is obtained by a fast update of the optimal segmentation between successive frames. No eye movement model is required being the procedure fast enough to obtain the current frame segmentation as one step update from the previous frame segmentation. (C) 2009 Elsevier Ireland Ltd. All rights reserve
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