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Feedback loop

About: Feedback loop is a research topic. Over the lifetime, 4441 publications have been published within this topic receiving 62638 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors investigated active damping of LCL-filter resonance in a grid-connected voltage-source converter with only grid-current feedback control and showed that the proposed damping technique with a negative high-pass filter along its damping path is equivalent to adding a virtual impedance across the grid-side inductance.
Abstract: This paper investigates active damping of LCL- filter resonance in a grid-connected voltage-source converter with only grid-current feedback control. Basic analysis in the s -domain shows that the proposed damping technique with a negative high-pass filter along its damping path is equivalent to adding a virtual impedance across the grid-side inductance. This added impedance is more precisely represented by a series RL branch in parallel with a negative inductance. The negative inductance helps to mitigate phase lag caused by time delays found in a digitally controlled system. The mitigation of phase-lag, in turn, helps to shrink the region of nonminimum-phase behavior caused by negative virtual resistance inserted unintentionally by most digitally implemented active damping techniques. The presented high-pass-filtered active damping technique with a single grid-current feedback loop is thus a more effective technique, whose systematic design in the z -domain has been developed in this paper. For verification, experimental testing has been performed with results obtained matching the theoretical expectations closely.

301 citations

Journal ArticleDOI
TL;DR: In this paper, a general small-signal model for current-programmed switching power stages is used for design-oriented analysis of a 150 W buck regulator and a 280 W boost regulator.
Abstract: A general small-signal model for current-programmed switching power stages is used for design-oriented analysis of a 150 W buck regulator and a 280 W boost regulator. The model, into which the current-programming minor feedback loop is absorbed, exposes the desired tendency towards 'constant' output current. The regulator voltage loop remains the only explicit feedback loop, allowing the regulator closed-loop properties to be easily obtained from those of the open-loop current-programmed power stage. The design-oriented analytic results allow easy inference of the effects of element changes on the regulator performance functions. Results are obtained for the regulator line-to-output transfer function (audio susceptibility) and output impedance. >

296 citations

Patent
25 Feb 2004
TL;DR: In this paper, a machine learning approach is applied to spam filters, and examples of both legitimate and junk/spam mail are obtained to generate sets of training data to classify items in connection with spam prevention in server or client-based architectures.
Abstract: The subject invention provides for a feedback loop system and method that facilitate classifying items in connection with spam prevention in server and/or client-based architectures. The invention makes uses of a machine-learning approach as applied to spam filters, and in particular, randomly samples incoming email messages so that examples of both legitimate and junk/spam mail are obtained to generate sets of training data. Users which are identified as spam-fighters are asked to vote on whether a selection of their incoming email messages is individually either legitimate mail or junk mail. A database stores the properties for each mail and voting transaction such as user information, message properties and content summary, and polling results for each message to generate training data for machine learning systems. The machine learning systems facilitate creating improved spam filter(s) that are trained to recognize both legitimate mail and spam mail and to distinguish between them.

292 citations

Proceedings ArticleDOI
07 Dec 2015
TL;DR: An entirely data-driven approach to estimating the 3D pose of a hand given a depth image is proposed, which outperforms state-of-the-art methods, and is efficient as the implementation runs at over 400 fps on a single GPU.
Abstract: We propose an entirely data-driven approach to estimating the 3D pose of a hand given a depth image. We show that we can correct the mistakes made by a Convolutional Neural Network trained to predict an estimate of the 3D pose by using a feedback loop. The components of this feedback loop are also Deep Networks, optimized using training data. They remove the need for fitting a 3D model to the input data, which requires both a carefully designed fitting function and algorithm. We show that our approach outperforms state-of-the-art methods, and is efficient as our implementation runs at over 400 fps on a single GPU.

291 citations

Journal ArticleDOI
TL;DR: In this article, a new concept of active vibration absorption for dynamic structures, delayed resonator, originates from a proportional position feedback excitation utilized on an otherwise conventional mass-spring-damper absorber.

288 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202376
202276
202183
2020171
2019126
2018163