Online Frequency Response Analysis: A Powerful Plug-in Tool for Compensation Design and Health Assessment of Digitally Controlled Power Converters

Bhardwaj, Manish; Choudhury, Shamim; Poley, Richard; Akin, Bilal

doi:10.1109/tia.2016.2522951

Cited by 34 publications

(28 citation statements)

References 16 publications

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“…In practice, the proposed online distance metrics can be used for diagnostics purposes for instance by considering a predetermined safety limits in region I. Moreover, the loop-transfer function could be estimated directly from the closed-loop experiment (Barkley and Santi, 2009), (Bhardwaj et al, 2016). These issues will be considered in the future research, and thus not further discussed in this work, where the main focus is to analyse and validate the feasibility of the proposed method for frequency response estimation.…”

Section: Loop-transfer Functionmentioning

confidence: 99%

Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

Nevaranta

Derammelaere

Parkkinen

et al. 2016

MIC

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Some of the most widely recognized online parameter estimation techniques used in different servomechanism are the extended Kalman filter (EKF) and recursive least squares (RLS) methods. Without loss of generality, these methods are based on a prior knowledge of the model structure of the system to be identified, and thus, they can be regarded as parametric identification methods. This paper proposes an on-line non-parametric frequency response identification routine that is based on a fixed-coefficient Kalman filter, which is configured to perform like a Fourier transform. The approach exploits the knowledge of the excitation signal by updating the Kalman filter gains with the known time-varying frequency of chirp signal. The experimental results demonstrate the effectiveness of the proposed online identification method to estimate a non-parametric model of the closed loop controlled servomechanism in a selected band of frequencies.

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Section: Loop-transfer Functionmentioning

confidence: 99%

Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

Nevaranta

Derammelaere

Parkkinen

et al. 2016

MIC

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“…Recently, many system identification approaches based on the frequency response have been proposed for the stability analysis of converters controllers [16]- [19]. These approaches typically consider the system of interest as a black-box model [16], [17] or a grey-box model [18], [19] and, when the error between the real system behavior and the corresponding model behavior is minimized, an accurate model is deemed to have been obtained. The black-box model, also known as non-parametric system identification technique, features a low complexity level and does not require prior knowledge of the model to be estimated.…”

Section: Introductionmentioning

confidence: 99%

Analysis of an Online Stability Monitoring Approach for DC Microgrid Power Converters

Khodamoradi

Liu

Mattavelli

et al. 2019

IEEE Trans. Power Electron.

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An on-line approach to evaluate and monitor the stability margins of dc microgrid power converters is presented in this paper. The discussed online stability monitoring technique (MT) is based on the Middlebrook's loop-gain measurement technique, adapted to the digitally controlled power converters. In this approach, a perturbation is injected into a specific digital control loop of the converter and after measuring the loop gain, its crossover frequency and phase margin are continuously evaluated and monitored. The complete analytical derivation of the model, as well as detailed design aspects, are reported. In addition, the presence of multiple power converters connected to the same dc bus, all having the stability monitoring unit, is also investigated. An experimental microgrid prototype is implemented and considered to validate the theoretical analysis and simulation results, and to evaluate the effectiveness of the digital implementation of the technique for different control loops. The obtained results confirm the expected performance of the stability monitoring tool in steady-state and transient operating conditions. The proposed method can be extended to generic control loops in power converters operating in dc microgrids.

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“…Adaptive and self-tuning controllers for switch mode power converter (SMPC) applications, based on system identification of the power converter parameters, are receiving increasing research attention [1][2][3]. This is in part due to the continuous fall in price, and improved processing performance of modern microprocessor platforms.…”

Section: Introductionmentioning

confidence: 99%

Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter

Ahmeid

Armstrong

Al‐Greer

et al. 2018

IEEE Trans. Power Electron.

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Online Frequency Response Analysis: A Powerful Plug-in Tool for Compensation Design and Health Assessment of Digitally Controlled Power Converters

Cited by 34 publications

References 16 publications

Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

Analysis of an Online Stability Monitoring Approach for DC Microgrid Power Converters

Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter

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