Real-Time Identification Using Adaptive Discrete Model

Autor:	J.J. Hirsch, P. Peltie
Rok vydání:	1973
Předmět:	Adaptive filter Identification (information) Noise Control theory Computer science Process (computing) Hyperstability Variance (accounting) Series and parallel circuits
Zdroj:	IFAC Proceedings Volumes. 6:290-297
ISSN:	1474-6670
DOI:	10.1016/s1474-6670(17)68202-8
Popis:	This paper presents a new method for real time identification using a discrete adaptive model. Synthesis of adaptive loops for model parameters is achieved by using the hyperstability concepts. Attention is focused on a special treatment of error between model and process outputs which take into account the feedback realized by adaptive loops. Algorithms are written for identification with parallel (output error method) and series parallel (equation error method) models. Performance of these methods are compared and simulation results of parameters variance and biasing in presence of noise are given. Moreover effects on convergence speed are described. Experimental results have been obtained on a heat-exchanger. In conclusion, an extension of this method to adaptive filtering is proposed and an application to very high noise-signal ratio measurements is given.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::23045f88221eadf99a38448b5b1f918b https://doi.org/10.1016/s1474-6670(17)68202-8 Zobrazit plný text záznamu