Global adaptive output feedback controllers with application to non‐linear friction compensation

In this paper, we consider a class of non‐linear systems in which a set of constant parameters is unknown and some state variables are not available for measurement. For such systems we provide a constructive procedure for the solution of the global adaptive tracking problem with dynamic partial state feedback. We illustrate an application of the control strategy to the adaptive non‐linear friction compensation of a DC motor servomechanism. We improve previous results in tow directions: we allow for a subset of the unmeasurable states to enter in a system non‐linearly; we consider systems which are linearly parametrized with respect to a set of unknown constant parameters. Copyright © 2002 John Wiley & Sons, Ltd.     

TGF-beta-induced apoptosis of cerebellar granule neurons is prevented by depolarization

The regulation of programmed cell death in the developing nervous system involves target-derived survival factors, afferent synaptic activity, and hormone- and cytokine-dependent signaling. Cultured immature cerebellar granule neurons die by apoptosis within several days in vitro unless maintained in depolarizing (high) concentrations of potassium (25 mM K+). Here we report that transforming growth factors (TGF)-beta1, -beta2, and -beta3 accelerate apoptosis of these neurons when maintained in physiological (low) K+ medium (5mM K+) as assessed by measures of viability, quantitative DNA fragmentation, and nuclear morphology. TGF-beta-induced apoptosis of these neurons is not blocked by CNTF and LIF, cytokines that enhance neuronal survival when applied alone, or by IGF-I, which prevents apoptosis upon potassium withdrawal. In contrast, neurons that differentiate in high K+ medium for several days in vitro acquire resistance to TGF-beta-mediated cell death. Granule neurons maintained in either low or high K+ medium produce latent, but not bioactive, TGF-beta1 and -beta2. Because neutralizing TGF-beta antibodies fail to augment survival of low K+ neurons, the cerebellar neurons are apparently unable to activate latent TGF-beta. Thus, apoptosis of low K+ neurons is not attributable to endogenous production of TGF-beta. Taken together, our data suggest that TGF-beta may limit the expansion of postmitotic neuronal precursor populations by promoting their apoptosis but may support survival of those neurons that have maturated, differentiated, and established supportive synaptic connectivity.     

Active state estimation for nonlinear systems: a neural approximation approach.

In this paper, we consider the problem of actively providing an estimate of the state of a stochastic dynamic system over a (possibly long) finite time horizon. The active estimation problem (AEP) is formulated as a stochastic optimal control one, in which the minimization of a suitable uncertainty measure is carried out. Toward this end, the use of the Renyi entropy as an information measure is proposed and motivated. A neural control scheme, based on the application of the extended Ritz method (ERIM) and on the use of a Gaussian sum filter (GSF), is then presented. Simulation results show the effectiveness of the proposed approach.     

Large band simulation of the wind speed for real time wind turbine simulators

In this paper, the authors propose two modeling procedures for wind speed simulation. These procedures could be implemented on the structure of a wind turbine simulator during studies concerning stand-alone or hybrid wind systems. The evolution of a horizontal wind speed has been synthesized taking into account two components. The medium- and long-term component is described by a power spectrum associated to a specific site. The turbulence component is assumed to be dependent on the medium- and long-term wind speed evolution. It is considered as a nonstationary process. Two simulation methods for this component, using rational and nonrational filters are proposed. In both procedures, the turbulence model is defined by two parameters, which are either obtained experimentally, or adopted a priori, according to information from the considered site. Numerical results and implementation aspects are also discussed.     

Timing and causality in process algebra

 There has been considerable controversy in concurrency theory between the ‘interleaving’ and ‘true concurrency’ schools. The former school advocates associating a transition system with a process which captures concurrent execution via the interleaving of occurrences; the latter adopts more complex semantic structures to avoid reducing concurrency to interleaving. In this paper we show that the two approaches are not irreconcilable. We define a timed process algebra where occurrences are associated with intervals of time, and give it a transition system semantics. This semantics has many of the advantages of the interleaving approach; the algebra admits an expansion theorem, and bisimulation semantics can be used as usual. Our transition systems, however, incorporate timing information, and this enables us to express concurrency: merely adding timing appropriately generalises transition systems to asynchronous transition systems, showing that time gives a link between true concurrency and interleaving. Moreover, we can provide a complete axiomatisation of bisimulation for our algebra; a result that is often problematic in a timed setting. Another advantage of incorporating timing information into the calculus is that it allows a particularly simple definition of action refinement; this we present. The paper concludes with a comparison of the equivalence we present with those in the literature, and an example system specification in our formalism. Received December 20, 1993/February 23, 1995     

DYRE: a DYnamic REconfigurable solution to increase GPGPU’s reliability

The Journal of Supercomputing - General-purpose graphics processing units (GPGPUs) are extensively used in high-performance computing. However, it is well known that these devices’...     

Learning control in spatial coordinates for the path-following of autonomous vehicles

We prove the existence of a P-type (proportional-type) space-learning control, which, on the basis of a kinematic third order nonlinear model of an autonomous nonholonomic vehicle and by a proper choice of the proportional control gain, guarantees asymptotic tracking of planar curves whose uncertain curvature is L$L$-periodic in the curvilinear abscissa. The behavior of a human driver, who repetitively learns the correct action from the past experience in the space, is mathematically reproduced. A stability analysis is presented while simulation results demonstrate the effectiveness of the presented approach.     

Network Externalities,Incumbent’s Competitive Advantage and the Degree of Openness of Software Start-Ups

This paper proposes a formal model that analyzes the degree of openness chosen by start-ups when entering the software industry. In line with the literature, we label as degree of openness the extent to which software start-ups mix open source (OS) and proprietary solutions in the portfolio of software products they offer. We relate the choice of the degree of openness to two key characteristics of the market segments in which software start-ups operate: the strength of the network externalities and the competitive advantage of the incumbent. Specifically, by modelling (price) competition between an incumbent and an entrant in two ways, i.e., the entrant is price-setter or price-taker, we derive the necessary condition(s) in terms of the strength of network externalities for observing the adoption of a business model that comprises the offering of both proprietary and OS solutions by the entrant (i.e., hybrid business model). Then, we highlight that, if a hybrid business model is the choice, the degree of openness chosen in equilibrium increases along with both the strength of the network externalities and the competitive advantage of the incumbent. This result holds indifferently whether the software start-up is modelled as a price-setter or a price-taker. An empirical test run on a sample of European start-ups in the software industry supports these theoretical predictions.     

Information Sharing Among Disaster Responders - An Interactive Spreadsheet-Based Collaboration Approach

Recent natural disasters have led crisis management organizations to revise their protocols so as to rely on the contribution of a wider range of actors, including simple citizens as well as expert operators, to support decision making activities. Reliable and timely information sharing among members of distributed teams of disaster responders has become paramount for the success of the overall crisis management process. In this paper we propose a crisis management system based on spreadsheet-mediated collaboration among on-site responders and decision makers. To share data a common spreadsheet artifact has been developed by using a participatory design approach which is accessed through mobile user interfaces. The evaluation results showed that the use of the spreadsheet artifact has resulted in more effective decision making relating to set of earthquake management scenarios in high-risk areas located in Italy.