Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas

Jaroslaw Figwer; Malgorzata Michalczyk; Teresa Główka

doi:10.1109/MMAR.2017.8046851

Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas

Department of Measurements and Control Systems (RAU/RAU2)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

In the paper a modification enabling acceleration of the rate of convergence for LMS-like on-line identification and adaptation algorithms is proposed. This is based on an artificial decaying of initial conditions in recursive identification as well as adaptation algorithms. The decaying is done using a set of the most recent measurements. Properties of the algorithms with the proposed modification are compared with non-accelerated identification and adaptation algorithms in simulations of a practical adaptive control system.

Original language	English
Title of host publication	2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	347-350
Number of pages	4
ISBN (Electronic)	9781538624029
DOIs	https://doi.org/10.1109/MMAR.2017.8046851
Publication status	Published - 19 Sept 2017
Event	22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017 - Miedzyzdroje, Poland Duration: 28 Aug 2017 → 31 Aug 2017

Publication series

Name	2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017

Conference

Conference	22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017
Country/Territory	Poland
City	Miedzyzdroje
Period	28/08/17 → 31/08/17

ASJC Scopus subject areas

Artificial Intelligence
Control and Optimization
Modeling and Simulation

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10.1109/MMAR.2017.8046851

Cite this

Figwer, J., Michalczyk, M., & Główka, T. (2017). Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas. In 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017 (pp. 347-350). Article 8046851 (2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MMAR.2017.8046851

Figwer, Jaroslaw ; Michalczyk, Malgorzata ; Główka, Teresa. / Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1 : Basic ideas. 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 347-350 (2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017).

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abstract = "In the paper a modification enabling acceleration of the rate of convergence for LMS-like on-line identification and adaptation algorithms is proposed. This is based on an artificial decaying of initial conditions in recursive identification as well as adaptation algorithms. The decaying is done using a set of the most recent measurements. Properties of the algorithms with the proposed modification are compared with non-accelerated identification and adaptation algorithms in simulations of a practical adaptive control system.",

author = "Jaroslaw Figwer and Malgorzata Michalczyk and Teresa G{\l}{\'o}wka",

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Figwer, J , Michalczyk, M & Główka, T 2017, Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas. in 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017., 8046851, 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017, Institute of Electrical and Electronics Engineers Inc., pp. 347-350, 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017, Miedzyzdroje, Poland, 28/08/17. https://doi.org/10.1109/MMAR.2017.8046851

Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas. / Figwer, Jaroslaw ; Michalczyk, Malgorzata ; Główka, Teresa.
2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 347-350 8046851 (2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In the paper a modification enabling acceleration of the rate of convergence for LMS-like on-line identification and adaptation algorithms is proposed. This is based on an artificial decaying of initial conditions in recursive identification as well as adaptation algorithms. The decaying is done using a set of the most recent measurements. Properties of the algorithms with the proposed modification are compared with non-accelerated identification and adaptation algorithms in simulations of a practical adaptive control system.

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Figwer J , Michalczyk M , Główka T. Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas. In 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 347-350. 8046851. (2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017). doi: 10.1109/MMAR.2017.8046851

Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas

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