24,650 research outputs found

    Optimization of ordinary differential systems with hysteresis

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    We investigate general control problems governed by ordinary differential systems involving hysteresis operators. Our main hypotheses are of continuity type, and we discuss existence results, discretization methods, and approximation approaches

    Averaging methods for design of spacecraft hysteresis damper

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    This work deals with averaging methods for dynamics of attitude stabilization systems. The operation of passive gravity-gradient attitude stabilization systems involving hysteresis rods is described by discontinuous differential equations. We apply recently developed averaging techniques for discontinuous system in order to simplify its analysis and to perform parameter optimization. The results obtained using this analytic method are compared with those of numerical optimization.This research is supported by the Portuguese Foundation for Science and Technologies (FCT), the Portuguese Operational Programme for Competitiveness Factors (COMPETE), the Portuguese Strategic Reference Framework (QREN),and the European Regional Development Fund (FEDER)

    Nonlinear vibration absorber optimal design via asymptotic approach

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    This paper tackles the classical problem of Vibration Absorbers (VAs) operating in the nonlinear dynamic regime. Since traditional linear VAs suffer from the drawback of a narrow bandwith and numerous structures exhibit nonlinear behavior, nonlinear absorbers are of practical interest. The resonant dynamic behavior of a nonlinear hysteretic VA attached to a damped nonlinear structure is investigated analytically via asymptotics and numerically via path following. The response of the reduced-order model, obtained by projecting the dynamics of the primary structure onto the mode to control, is evaluated using the method of multiple scales up to the first nonlinear order beyond the resonance. Here, the asymptotic response of the two-degree-of-freedom system with a 1:1 internal resonance is shown to be in very close agreement with the results of path following analyses. The asymptotic solution lends itself to a versatile optimization based on differential evolutionary

    Memristors for the Curious Outsiders

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    We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to machine learning and neural computation.Comment: Perpective paper for MDPI Technologies; 43 page

    A Programmable Neural Oscillator Cell

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    A programmable analog neural oscillator cell architecture is presented. The proposed neuron circuit is of hysteretic neural nature with its implementation based on operational transconductance amplifiers (OTA's). The hysteresis loop as well as the frequency of oscillation are voltage (or current) dependent. The architecture, which involves two OTA's, a current mirror, a capacitor, a diode, and a resistor is very suitable for monolithic integrated circuits. Experimental results confirm the expected flexibility of the synthetic neuron
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