A Tutorial On Multiple Model Least-Squares and Augmented UD Identification
1995 (English)Report (Other academic)
The augmented UD identification (AUDI) is a family of new identification algorithms that are based on some well-known matrix decomposition and updating techniques. Compared with conventional least-squares methods, the AUDI methods are conceptually more concise, computationally more efficient, numerically more robust and application-wise more complete. As a result, AUDI is recommended as a complete replacements for conventional recursive least-squares in all parameter estimation and system identification applications. This tutorial paper presents an overview of the AUDI concept, implementation and applications. The multiple model least-squares (MMLS) method, which is a fundamental reformulation and an efficient implementation of the basic least-squares method, is discussed first. Some application examples of the MMLS/AUDI are presented to demonstrate the versatility and reliability of this type of algorithms.
Place, publisher, year, edition, pages
Linköping: Linköping University , 1995. , 64 p.
LiTH-ISY-R, ISSN 1400-3902 ; 1710
Parameter estimation, System identification, Least-squares, UD factorization, Multiple model least-squares (MMLS), Augmented UD identification (AUDI)
IdentifiersURN: urn:nbn:se:liu:diva-55193ISRN: LiTH-ISY-R-1710OAI: oai:DiVA.org:liu-55193DiVA: diva2:315781