Real-Time Implementation of Lyapunov Stability Theory-Based Adaptive Filter on FPGA

Engin Cemal MENGÜÇ; Nurettin ACIR

doi:10.1587/transele.E99.C.129

Real-Time Implementation of Lyapunov Stability Theory-Based Adaptive Filter on FPGA

Engin Cemal MENGÜÇ, Nurettin ACIR

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The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.

Publication: IEICE TRANSACTIONS on Electronics Vol.E99-C No.1 pp.129-137

Publication Date: 2016/01/01

Publicized

Online ISSN: 1745-1353

DOI: 10.1587/transele.E99.C.129

Type of Manuscript: PAPER

Category: Storage Technology

Authors

Engin Cemal MENGÜÇ
Nigde University
Nurettin ACIR
Bursa Technical University

Keyword

Lyapunov stability theory, adaptive filter, field programmable gate arrays, hardware implementation, software implementation

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Engin Cemal MENGÜÇ, Nurettin ACIR, "Real-Time Implementation of Lyapunov Stability Theory-Based Adaptive Filter on FPGA" in IEICE TRANSACTIONS on Electronics, vol. E99-C, no. 1, pp. 129-137, January 2016, doi: 10.1587/transele.E99.C.129.
Abstract: The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.
URL: https://globals.ieice.org/en_transactions/electronics/10.1587/transele.E99.C.129/_p

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@ARTICLE{e99-c_1_129,
author={Engin Cemal MENGÜÇ, Nurettin ACIR, },
journal={IEICE TRANSACTIONS on Electronics},
title={Real-Time Implementation of Lyapunov Stability Theory-Based Adaptive Filter on FPGA},
year={2016},
volume={E99-C},
number={1},
pages={129-137},
abstract={The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.},
keywords={},
doi={10.1587/transele.E99.C.129},
ISSN={1745-1353},
month={January},}

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TY - JOUR
TI - Real-Time Implementation of Lyapunov Stability Theory-Based Adaptive Filter on FPGA
T2 - IEICE TRANSACTIONS on Electronics
SP - 129
EP - 137
AU - Engin Cemal MENGÜÇ
AU - Nurettin ACIR
PY - 2016
DO - 10.1587/transele.E99.C.129
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E99-C
IS - 1
JA - IEICE TRANSACTIONS on Electronics
Y1 - January 2016
AB - The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.
ER -