Abstract
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 an 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 Bányász/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.
demonstrate an efficient and cost effective explicit self-tuning
controller, the proposed estimation algorithm (PUKF) is
embedded with a Bányász/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.
Original language | English |
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Pages (from-to) | 8081-8090 |
Number of pages | 10 |
Journal | IEEE Transactions on Power Electronics |
Volume | 33 |
Issue number | 9 |
Early online date | 1 Nov 2017 |
DOIs | |
Publication status | Published - Sept 2018 |
Bibliographical note
© Copyright 2017 IEEE - All rights reserved.Keywords
- System Identification
- Switch Mode Power Converters
- Digital Control
- Parametric Estimation
- Kalman Filter
- Self-tuning Controller