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

Lookup NU author(s): Dr Mohamed Ahmeid, Dr Matthew Armstrong, Dr Maher Al-Greer, Dr Shady Gadoue



IEEE In this paper, a partial update Kalman Filter (PUKF) is presented for the real-time parameter estimation of a DC-DC switch-mode power converter (SMPC). The proposed estimation algorithm is based on a novel combination between the classical Kalman filter and a M-Max partial adaptive filtering technique. The proposed PUKF offers a significant reduction in computational effort compared to the conventional implementation of the Kalman Filter (KF), with 50% less arithmetic operations. Furthermore, the PUKF retains comparable overall performance to the classical KF. To demonstrate an efficient and cost effective explicit self-tuning controller, the proposed estimation algorithm (PUKF) is embedded with a B?ny?sz/Keviczky PID controller to generate a new computationally light self-tuning controller. Experimental and simulation results clearly show the superior dynamic performance of the explicit self-tuning control system compared to a conventional pole placement design based on a pre-calculated average model.

Publication metadata

Author(s): Ahmeid M, Armstrong M, Al-Greer M, Gadoue S

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Power Electronics

Year: 2018

Volume: 33

Issue: 9

Pages: 8081-8090

Print publication date: 01/09/2018

Online publication date: 01/11/2017

Acceptance date: 02/04/2016

Date deposited: 20/11/2017

ISSN (print): 0885-8993

ISSN (electronic): 1941-0107

Publisher: IEEE


DOI: 10.1109/TPEL.2017.2768618


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