Abstract

To achieve high-performance control of modern dc-dc converters, using direct digital design techniques, an accurate discrete model of the converter is necessary. In this paper, a new parametric system identification method, based on a Kalman filter (KF) approach is introduced to estimate the discrete model of a synchronous dc-dc buck converter. To improve the tracking performance of the proposed KF, an adaptive tuning technique is proposed. Unlike many other published schemes, this approach offers the unique advantage of updating the parameter vector coefficients at different rates. The proposed KF estimation technique is experimentally verified using a Texas Instruments TMS320F28335 micro-controller platform and synchronous step-down dc-dc converter. Results demonstrate a robust and reliable real-time estimator. The proposed method can accurately identify the discrete coefficients of the dc-dc converter. This paper also validates the performance of the identification algorithm with time-varying parameters, such as an abrupt load change. The proposed method demonstrates robust estimation with and without an excitation signal, which makes it very well suited for real-time power electronic control applications. Furthermore, the estimator convergence time is significantly shorter compared to many other schemes, such as the classical exponentially weighted recursive least-squares method.

IEEE TRANSACTIONS ON POWER ELECTRONICS

Volume: 32

Issue: 7

Pages: 5666-5674

DOI: 10.1109/TPEL.2016.2606417

Published: JUL 2017

Author Information

Reprint Address: Ahmeid, M (reprint author)

Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England.

Addresses:

[ 1 ] Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
[ 2 ] Alexandria Univ, Dept Elect Engn, Fac Engn, Alexandria 21544, Egypt

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Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA

Categories / Classification

Research Areas:Engineering

Web of Science Categories:Engineering, Electrical & Electronic

Document Information

Document Type:Article

Language:English

Accession Number: WOS:000396134300054

ISSN: 0885-8993

eISSN: 1941-0107

Other Information

IDS Number: EN6SS

Cited References in Web of Science Core Collection: 25

Times Cited in Web of Science Core Collection: 0