Browse by author
Lookup NU author(s): Dr Maher Al-Greer,
Dr Matthew Armstrong,
Professor Damian Giaouris
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
This paper introduces a novel technique for on-line system identification. Specific attention is given to the parameter estimation of dc-dc Switched Mode Power Converters (SMPC), however, the proposed method can be applied to many alternative applications where efficient and accurate parameter estimation is required. The proposed technique is computationally efficient, based around a Dichotomous Coordinate Descent (DCD) algorithm, and uses an infinite impulse response (IIR) adaptive filter as the plant model. The system identification technique reduces the computational complexity of existing Recursive Least Squares (RLS) algorithms. Importantly, the proposed method is also able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Simulation analysis and validation based on experimental data obtained from a prototype synchronous dc-dc buck converter is presented. Results clearly demonstrate that the estimated parameters of the dc-dc converter are a very close match to those of the experimental system. The approach can be directly embedded into adaptive and self-tuning digital controllers to improve the control performance of a wide range of industrial and commercial applications.
Author(s): Algreer M, Armstrong M, Giaouris D
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Power Electronics
Print publication date: 01/04/2012
ISSN (print): 0885-8993
ISSN (electronic): 1941-0107
Altmetrics provided by Altmetric