Accelerating the rate of convergence for LMS-like on-line identification and adaptation algorithms. Part 1: Basic ideas
| Autor: | Teresa Glowka, Jaroslaw Figwer, Małgorzata I. Michalczyk |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Adaptive control Computer science 02 engineering and technology Set (abstract data type) 030507 speech-language pathology & audiology 03 medical and health sciences Identification (information) Acceleration 020901 industrial engineering & automation Rate of convergence Line (geometry) Convergence (routing) 0305 other medical science Adaptation (computer science) Algorithm |
| Zdroj: | MMAR |
| DOI: | 10.1109/mmar.2017.8046851 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|