Aim: To evaluate Patients and Methods: 27 newborns (13 F, mean GA : 277 days, mean BW: 3890 g) were included ; FHa and IEA was evaluated, a blood sample collected from cord blood to measure serum ECP, nasal and rectal tampons executed at birth to count eosinophyls. Statist ical analysis: Anova test and t-student test. Results: 11 newborns had FHa, and 2 had IEA (group A). We attributed a score from 0 to 3 at the FHa and the IEA. Group A got 11 points, while the group without a family risk of atopy got 4 points. The mean values of ECP value was 65.5 µ/ml in group A and 7.8 µ/ml in group B (p< 0.05). The exposition frequency was 61% in group A and 33% in group B. The cytologic research did not find any eosinophilic cell in rectal or nasal mucosa. Conclusions: The difference of exposition frequencies between the 2 groups suggests more intensive eosinofilic activation in exposed newborns. The identification of newborns at “extremely high atopic risk” (ECP>13,5 µg/l, FHa and IEA) with the assignment of a diagnostic score in clinical practice can be useful to apply early environmental and dietary prevention measures.

The detection of events in video streams is a central task in the automatic vision paradigm, and spans heterogeneous fields of application from the surveillance of the environment, to the analysis of scientific data. Actually, although well captured by intuition, the definition itself of event is somewhat hazy and depending on the specific application of interest. In this work, the approach to the problem of event detection is different in nature. Instead of defining the event and searching for it within the data, a normality space of the scene is built from a chosen learning sequence The event detection algorithm works by projecting any newly acquired image onto the normality space so as to calculate a distance from it that represents the innovation of the new frame, and defines the metric for triggering an event alert.

We formulate the problem of estimating the motion of a rigid object viewed under perspective projection as the identification of a dynamic model in Exterior Differential form with parameters on a topological manifold. We first describe a general method for recursive identification of nonlinear implicit systems using prediction error criteria. The parameters are allowed to move slowly on some topological (not necessarily smooth) manifold. The basic recursion is solved in two different ways: one is based on a simple extension of the traditional Kalman Filter to nonlinear and implicit measurement constraints, the other may be regarded as a generalized "Gauss-Newton" iteration, akin to traditional Recursive Prediction Error Method techniques in linear identification. A derivation of the "Implicit Extended Kalman Filter" (IEKF) is reported in the appendix. The ID framework is then applied to solving the visual motion problem: it indeed is possible to characterize it in terms of identification of an Exterior Differential System with parameters living on a Co topological manifold, called the "essential manifold". We consider two alternative estimation paradigms. The first is in the local coordinates of the essential manifold: we estimate the state of a nonlinear implicit model on a linear space. The second is obtained by a linear update on the (linear) embedding space followed by a projection onto the essential manifold. These schemes proved successful in performing the motion estimation task, as we show in experiments on real and noisy synthetic image sequences.

This paper addresses the dynamic inversion problem for planar and spatial vehicles having as configuration space the Lie groups SE(2) and SE(3), respectively. For vehicles whose dynamics is invariant with respect to the group action and satisfy suitable conditions, we show that the dynamic inversion problem can be reduced and studied in the Lie algebra of the group. We outline a procedure to solve the reduced dynamic inversion problem, showing that one need to find, at each instant of time, the input value that satisfies a set of nonlinear constraints depending on current state and desired maneuver. Simulation examples of a two-wheel vehicle and a neutrally buoyant autonomous underwater vehicle (AUV) are provided to show effectiveness of the method.

In this paper we provide a new strategy to explore feasible trajectories of nonlinear systems, that is to find curves that satisfy the dynamics as well as point-wise state-input constraints. This strategy is interesting itself in understanding the behavior of the system especially in critical conditions, and represents a useful tool that can be used to perform trajectory tracking in presence of constraints. The strategy is based on a novel optimization technique, introduced by Hauser, to find regularized solutions for point-wise constrained optimization of trajectory functionals. The strategy is applied to the PVTOL, a simplified model of a real aircraft that captures the main features and challenges of the real model.

The development of a motorcycle driver for virtual prototyping applications is discussed. The driver is delivered with a commercial multibody code as a tool for performing closed-loop maneuvers with virtual motorcycle models. The closed-loop controller is developed with a qualitative analysis of how a human rider controls a motorcycle. The analysis concerns handling and maneuverability, which are relevant for real and virtual vehicle performance evaluation. A motorcycle model for control design and a controller structure are developed. The model is based on a mathematical representation of common-sense rules of motorcycle riding. The virtual rider is then tested in various operating conditions to assess whether the control requirements are achieved. Criteria for evaluating driver models are briefly discussed

T he design and development of modern road vehicles calls for a combination of disparate engineering disciplines. Customer requirements include stringent performance, reliability, and safety specifications. If these requirements are to be met in a cost-effective manner, modern design and manufacture processes must be used. In addition, these processes must be able to produce new vehicles in a competitive time frame. In the last decade, the intensive use of information technologies has proven to be effective in meeting these requirements; in particular, control, simulation, and design methodologies have been instrumental in improving vehicle performance. Control system contributions include antilock braking and sophisticated engine management systems, which are now commonplace. The crucial role played by information technologies such as integrated development tools goes beyond computer-aided design aids to include sophisticated computer-based prediction and analysis tools. New vehicle components and assemblies can now be created, and their performance predicted, in virtual simulation environments. Indeed, complete vehicles can be assembled and evaluated using performance criteria ranging from fatigue durability to handling and performance characteristics prior to the physical manufacturing of the vehicle’s components. When used in combination with physical testing systems, computer-aided engineering and virtual prototyping tools offer the potential for the further reduction of vehicle development cycle times and costs since these tools facilitate a high level of product maturity at the conceptual stage of the development process. Computeraided engineering paradigms unite designers and analysts in a common framework in which computer-aided design and powerful simulation packages are now combined. Control engineers are already at ease in this environment, since the use and development of software simulation packages are standard parts of their everyday professional lives. We expect the control engineering community to continue to contribute to technological progress in the automotive industry by working on theoretical and applied challenges of which simulation and virtual prototyping tools are an integral part. Although the motorcycle industry lags behind the automotive industry with respect to economic importance, the number of motorcycles in circulation is large and in some countries surpasses the number of cars on the road. Scooters, mopeds, and light motorcycles are in high demand in urban areas due to their ability to avoid traffic congestion as well as their low fuel and running costs. In Italy, more than 3.5 million motorcycles are in circulation with AN INTRODUCTION TO THE SPECIAL SECTION

We explore the solutions of the driven inverted pendulum system l\#0308\=gsinφ-al(t)cosτ where al(·) is a bounded lateral acceleration. We show that, for lateral accelerations that are constant before some initial time, an inverted trajectory always exists and remains within a diamond shaped region in the state space. Functional analytic techniques are also developed to provide further insight into the nature of the inverted pendulum trajectories. Associated to the driven inverted pendulum is a time varying linear system. We show that this system always possesses an exponential dichotomy, allowing for the development of a successive approximation algorithm for finding the desired inverted pendulum trajectory. We show that the curve obtained from one iteration of this algorithm is a very good estimate of the required inverted trajectory. As that curve is obtained by filtering the quasi-static angle trajectory by a noncausal time varying low pass filter with weighting function with a shape similar to h(t) = exp−α0|t|, we find that the current pendulum angle is influenced by the values of the lateral acceleration within only a few seconds of the current time. These results are important as the driven inverted pendulum is a common susbsystem in systems ranging from motorcycles and bicycles to rockets and aircaft.

Nowadays there exist a vast literature on the lateral control of cars with different objectives ranging from stability control to autonomous driving on intelligent highways or virtual prototypes in CAE tools. The synthesis of the proposed controllers is based, in most papers, on standard models of the vehicle lateral dynamics such as the one-track model described in [2]. The art of the control engineer has always been the choice of the right model for control design. Here, we describe the properties of a different model of the vehicle in terms of a recently introduced concept of kinematic reducibility. We claim that this model is best for control design and we illustrate the architecture of a controller previously developed by the authors. Finally, we show the controller behaviour in various simulations of aggressive maneuvers.

Abstract— In this paper, we study the trajectory space of the PVTOL aircraft. We show that, due to the non-minimum phase nature of the system, more aggressive trajectories may be tracked with respect to the simplified differentially flat model. Given bounded C, trajectories of the center of gravity, we,show that there exists a bounded,roll trajectory which implements them. We compute an approximation of such roll trajectory using a Newton method for nonlinear optimization based on a trajectory tracking projection operator.

Recent experiments on frogs and rats, have led to the hypothesis that sensory-motor systems are organized into a finite number of linearly combinable modules; each module generates a motor command that drives the system to a predefined equilibrium. Surprisingly, in spite of the infiniteness of different movements that can be realized, there seems to be only a handful of these modules. The structure can be thought of as a vocabulary of "elementary control actions". Admissible controls, which in principle belong to an infinite dimensional space, are reduced to the linear vector space spanned by these elementary controls. In the present paper we address some theoretical questions that arise naturally once a similar structure is applied to the control of nonlinear kinematic chains. First of all, we show how to choose the modules so that the system does not loose its capability of generating a "complete" set of movements. Secondly, we realize a "complete" vocabulary with a minimal number of elementary control actions. Subsequently, we show how to modify the control scheme so as to compensate for parametric changes in the system to be controlled. Remarkably, we construct a set of modules with the property of being invariant with respect to the parameters that model the growth of an individual. Robustness against uncertainties is also considered showing how to optimally choose the modules equilibria so as to compensate for errors affecting the system. Finally, the motion primitive paradigm is extended to locomotion and a related formalization of internal (proprioceptive) and external (exteroceptive) variables is given.

In this paper we address the problem of controlling a disk, rolling on a horizontal plane, using only throttle as control input. The disk is supposed to follow an assigned path in the plane. The problem is difficult because of the high order of underactuation and of the instability of the system. The controller is based upon an internal manifold and a receding horizon technique. By using a backstepping control technique the controller tracks a lean angle trajectory. The lean angle reference trajectory is generated at each instant through a receding horizon algorithm and it is such that, if followed, the system tracks the assigned path with a bounded error.

We introduce a novel perspective for viewing the “ego-motion reconstruction” problem as the estimation of the state of a dynamical system having an implicit measurement constraint and unknown inputs. Such a system happens to be “linear”, but it is defined on a space (the “Essential Manifold”) which is not a linear (vector) space.We propose two recursive schemes for performing the estimation task: the first consists in “flattening the space” and solving a nonlinear estimation problem on the flat (euclidean) space. The second consists in viewing the system as embedded in a larger euclidean space, and solving at each step a linear estimation problem on a linear space, followed by a “projection” onto the Essential Manifold.Both schemes output motion estimates together with the joint second order statistics of the estimation error, which can be used by any “structure from motion” module which incorporates motion error [18, 22] in order to estimate 3D scene structure.Experiments are presented with real and synthetic image sequences.