1,721,003 research outputs found
Two-age-structured covid-19 epidemic model: Estimation of virulence parameters to interpret effects of national and regional feedback interventions and vaccination
Full text linkThe COVID-19 epidemic has recently led in Italy to the implementation of different external strategies in order to limit the spread of the disease in response to its transmission rate: strict national lockdown rules, followed first by a weakening of the social distancing and contact reduction feedback interventions and finally the implementation of coordinated intermittent regional actions, up to the application, in this last context, of an age-stratified vaccine prioritization strategy. This paper originally aims at identifying, starting from the available age-structured real data at the national level during the specific aforementioned scenarios, external-scenario-dependent sets of virulence parameters for a two-age-structured COVID-19 epidemic compartmental model, in order to provide an interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19
Linear Repetitive Learning Controls for Robotic Manipulators by Padé Approximants
Full text linkThe aim of this brief is to present the use of [m, m]-Pade approximants in the implementation of repetitive learning controls for the asymptotic joint position tracking of robotic manipulators with uncertain dynamics and periodic position reference signals (with known period). The resulting linear learning controls, which are derived through a detailed stability proof (involving the use of a suitable Lyapunov-like function), are described by transfer functions exhibiting all their poles with a negative real part while allowing of experimental improvements in the output tracking errors as the approximation order m increases. Analyses from both theoretical and experimental points of view are included. Such control laws are good candidates to be implemented in industrial robot control units for repetitive tasks in place of classical proportional-integral-derivative (PID) controls
PMSM-Model-Based Sensorless Control of Hybrid Stepper Motors: Performance and Robustness to Parameters Dispersion
No full textExtended Kalman Filters (EKFs), Phase Locked Loops (PLLs), and Stator Flux Observers (SFOs) are widely used for sensorless control of Permanent Magnet Synchronous Motors (PMSMs) drives. Their use (in their most advanced version) is here extended, on the basis of model analogies and suitably-guaranteed closed loop stability properties, to the sensorless speed regulation control of Hybrid Stepper Motors (HSMs), in which position and speed sensors are not employed to reduce costs and increase robustness with respect to high temperature and high-vibration environments. Both realistic simulations and experimental results demonstrate the feasibility of the proposed methods in terms of closed-loop performance and robustness to parameters mismatch
Stator Flux Observer for the Sensorless Speed Control of Synchronous Machines with Uncertain Torque Constant
No full textIn this paper, a recently designed adaptive stator flux observer (SFO), which provides estimates of rotor position and torque constant for surface mounted permanent magnet synchronous machines (PMSMs), is included in a speed sensorless control. Simulations and experimental results are carried out in order to evaluate the robustness of the whole control architecture with respect to uncertainties in the electrical parameters of the motor, as well as to the mismatch between the actual stator voltages imposed to the PMSM and the ones used for the observer, especially when low speeds are involved
Stator Flux Observers for Speed-Controlled PMSMs in Low-Speed Sensorless Applications: Comparative Tests and Hybrid Strategy
No full textIn-depth performance analysis of stator flux observers (SFOs) is carried out, in the very low-speed range, for sensorless speed-controlled drives based on permanent magnet synchronous machines (PMSMs), in the presence of no idealities of the voltage source inverter (VSI) and uncertainties in the motor electrical parameters. The original contribution of this brief is twofold. First, it relies on the presentation of experiments, within this framework, which comparatively illustrate the closed-loop performance of: 1) a stator flux (open-loop) estimator with a low-pass filter (LPF), endowed with an additional phase shift and magnitude compensation based on the estimation of machine speed and 2) two adaptive observers constituting the most recent representatives of the class of the theoretically based contributions for PMSMs. While the former can achieve more satisfactory results when speed variations are relatively small, its performance degrades - when speed variations become relevant - when compared to the aforementioned adaptive SFOs which, in turn, still exhibit the advantage of estimating an additional critical parameter (under reliable knowledge of the motor inductance) related to demagnetization effects. Indeed, the crucial role of the adaptation is highlighted throughout the sections, while the conditions underlying the design and the stability proofs of such adaptive SFOs are shown to provide actually effective tools and restrictions under which satisfactory performances for the considered adaptive SFOs can be achieved in practice. Second, the common notation of the brief finally leads to the original formulation of a new comprehensive set of equations that simultaneously covers all the tested solutions and defines a hybrid strategy that might be very effective in practical applications
A new nonlinear control of an active rectifier for variable speed generating units
No full textThis paper deals with a newly conceived (state-feedback) nonlinear control strategy for an active rectifier that is supplied by a Permanent Magnet Synchronous Generator (PMSG). The aim of the proposed control strategy is properly regulate the DC-link voltage within a wide range of system operating conditions by: (i) taking into account a sufficiently rich model, in which the classical simplification – imposing to the DC voltage dynamics a relative degree equal to two – is avoided (so that the input power is not assumed to supply instantaneously the sum of load power and charging rate of the capacitor energy, with the resistance loss and the switching device loss being neglected); (ii) resorting to neither input–output linearizing strategies (involving the DC-link voltage regulation error) that lead to unstable regulation dynamics nor to simplifying design assumptions that overlook derivatives of intermediate reference signals; (iii) avoiding the computational-effort-requirements of Model Predictive Control (MPC) techniques. Simulation and Hardware in the loop (HIL) results illustrate the effectiveness of the proposed control – exhibiting a rather simple structure while guaranteeing local exponential stability for the resulting error system – in terms of Total Harmonic Distortion (THD) and controller response to load and DC voltage reference steps: high band-width and good steady-state waveforms are achieved. Robustness issues and control adaptiveness with respect to uncertain model parameters are also finally addressed
Padé-based-Repetitive Learning Current-Control for Voltage Source Inverters
No full textThe paper poses the basis for the application of the Padé-based-repetitive learning control to power converters, in all the scenarios where a periodic reference signal is to be tracked. Compared to standard repetitive schemes, the new relevant feature of the proposed control is that the learning scheme is reduced to a simple intrinsically stable transfer function, whose poles lie on the left-hand-side of the complex plane. Hence, storing a considerable amount of samples is no longer required, while resetting procedures are no longer involved. The Padé-based-repetitive control has a simple structure, while being able to automatically compensate for any periodic disturbance signals coming from external generators and dead-time. A stability analysis is reported, providing a useful guidance to tune the control parameters. Simulation results are presented to illustrate the effectiveness of the proposed algorithm. © 2018 IEEE
Synchronization control of DC motors through adaptive disturbance cancellation techniques
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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