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Institution

Polytechnic University of Milan

EducationMilan, Italy
About: Polytechnic University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Computer science & Finite element method. The organization has 18231 authors who have published 58416 publications receiving 1229711 citations. The organization is also known as: PoliMi & L-NESS.


Papers
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Journal ArticleDOI
TL;DR: It is shown that by invoking the redundancy properties induced by the descriptor formulation, combined with some convexifying techniques, the existence of the desired reliable controller can be explicitly determined by the solution of a convex optimization problem.
Abstract: This article studies the robust and reliable $\mathscr {H}_{\infty }$ static output feedback (SOF) control for nonlinear systems with actuator faults in a descriptor system framework. The nonlinear plant is characterized by a discrete-time Takagi-Sugeno (T-S) fuzzy affine model with parameter uncertainties, and the Markov chain is utilized to describe the actuator-fault behaviors. Specifically, by adopting a state-output augmentation approach, the original system is firstly reformulated into the descriptor fuzzy affine system. Based upon a novel piecewise Markovian Lyapunov function (LF), the $\mathscr {H}_{\infty }$ performance analysis condition for the underlying system is then presented, and furthermore the robust and reliable SOF controller synthesis is carried out. It is shown that by invoking the redundancy properties induced by the descriptor formulation, combined with some convexifying techniques, the existence of the desired reliable controller can be explicitly determined by the solution of a convex optimization problem. Finally, simulation studies are applied to confirm the effectiveness of the developed method.

316 citations

Journal ArticleDOI
TL;DR: A reconfiguration scheme, based on higher order sliding mode (HOSM) observer, is proposed in the event of sensor faults/failures to maintain a good control performance and is presented to demonstrate the validity of the proposed fault-detection scheme.
Abstract: This paper investigates the problem of automatic speed tracking control of an electric vehicle (EV) that is powered by a permanent-magnet synchronous motor (PMSM). A reconfiguration scheme, based on higher order sliding mode (HOSM) observer, is proposed in the event of sensor faults/failures to maintain a good control performance. The corresponding controlled motor output torque drives EVs to track the desired vehicle reference speed for providing uninterrupted vehicle safe operation. The effectiveness of the overall sensor fault-tolerant speed tracking control is highlighted when an EV is subjected to disturbances like aerodynamic load force and road roughness using high-fidelity software package CarSim. Experiments with a 26-W, three-phase PMSM are presented to demonstrate the validity of the proposed fault-detection scheme.

315 citations

Journal ArticleDOI
TL;DR: In this paper, a set of ground motion prediction equations (GMPEs) were derived for the geometrical mean of the horizontal components and the vertical, considering the latest release of the strong motion database for Italy.
Abstract: We present a set of ground motion prediction equations (GMPEs) derived for the geometrical mean of the horizontal components and the vertical, considering the latest release of the strong motion database for Italy. The regressions are performed over the magnitude range 4–6.9 and considering distances up to 200 km. The equations are derived for peak ground acceleration (PGA), peak ground velocity (PGV) and 5%-damped spectral acceleration at periods between 0.04 and 2 s. The total standard deviation (sigma) varies between 0.34 and 0.38 log10 unit, confirming the large variability of ground shaking parameters when regional data sets containing small to moderate magnitude events (M < 6) are used. The between-stations variability provides the largest values for periods shorter than 0.2 s while, for longer periods, the between-events and between-stations distributions of error provide similar contribution to the total variability.

315 citations

Journal ArticleDOI
TL;DR: The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs) to accurately approximate the coefficients of the reduced model.

315 citations

Journal ArticleDOI
TL;DR: In this article, the interaction of NO, NO2, or NO/O2 mixtures with Pt/Al2O3 and Ba/Al 2O3 catalysts has been investigated by IR spectroscopy and temperature-programmed desorption.
Abstract: The interaction of NO, NO2, or NO/O2 mixtures with Pt/Al2O3, Ba/Al2O3, and Pt−Ba/Al2O3 catalysts has been investigated by IR spectroscopy and temperature-programmed desorption. Upon NO interaction, small amounts of nitrites, nitrates, and hyponitrite species were formed on the Ba-containing samples. The NOx storage capacity of the catalysts was highly enhanced upon adsorption of NO/O2 mixtures and further upon NO2 admission. Upon adsorption of NO/O2 on Pt/Al2O3 sample nitrites, nitrates and NO2δ+ species were mainly formed, showing a moderate thermal stability. Barium markedly increased the amount and stability of the stored NOx species, which were bidentate and monodentate nitrites and, in minor amounts, nitrates. Nitrites were removed below 750 K and/or transformed into ionic Ba nitrates, stable up to 800−900 K. Upon NO2 adsorption, huge amounts of nitrates, but no nitrites, were formed on all the samples. Also in this case, Ba increased the amount and stability of the stored NOx species. The nature and...

314 citations


Authors

Showing all 18743 results

NameH-indexPapersCitations
Alex J. Barker132127384746
Pierluigi Zotto128119778259
Andrea C. Ferrari126636124533
Marco Dorigo10565791418
Marcello Giroletti10355841565
Luciano Gattinoni10361048055
Luca Benini101145347862
Alberto Sangiovanni-Vincentelli9993445201
Surendra P. Shah9971032832
X. Sunney Xie9822544104
Peter Nijkamp97240750826
Nicola Neri92112241986
Ursula Keller9293433229
A. Rizzi9165340038
Martin J. Blunt8948529225
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023302
2022813
20214,152
20204,301
20193,831
20183,767