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Application of a bounded‐error on‐line estimation algorithm to robotics systems
Author(s) -
Canudas Wit C. De
Publication year - 1994
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.4480080107
Subject(s) - bounded function , a priori and a posteriori , mechanical system , context (archaeology) , algorithm , system identification , line (geometry) , recursive least squares filter , control theory (sociology) , robotics , estimation theory , least squares function approximation , computer science , mathematics , identification (biology) , artificial intelligence , robot , adaptive filter , data modeling , statistics , botany , geometry , control (management) , epistemology , biology , mathematical analysis , paleontology , philosophy , database , estimator
This paper shows how bounded‐error on‐line estimation algorithms can be applied in the context of parameter identification of mechanical structures. the modified exponentially weighted recursive least‐squares (MEW‐RLS) estimation algorithm proposed by Canudas de Wit and Carrillo is used in connection with models of mechanical systems with state‐dependent disturbances. These disturbances are provoked on one hand by simplified friction models and on the other hand by the particular model formulation of the multivariable Lagrange mechanical systems. A priori knowledge on the physics of these systems is used to derive upper bounds on the model disturbances, which are needed for the application of the algorithm.