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On‐line parameter estimation for a class of time‐varying continuous systems with bounded disturbances
Author(s) -
Chen Jie,
Zhang Guozhu,
Li Zhiping
Publication year - 2011
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.1188
Subject(s) - bounded function , robustness (evolution) , mathematics , euclidean distance , polynomial , estimation theory , norm (philosophy) , control theory (sociology) , line (geometry) , mathematical optimization , computer science , algorithm , mathematical analysis , artificial intelligence , control (management) , biochemistry , chemistry , geometry , political science , law , gene
In this paper, we proposed an on‐line parameter estimation algorithm for a class of time‐varying continuous systems with bounded disturbance. In this method, a novel polynomial approximator with a bounded regressor vector is constructed and utilized to approximate the time‐varying parameters. The direct least‐squares algorithm is employed to acquire the on‐line estimates, so that several useful properties of the direct estimation, such as fast convergence and robustness to the bounded disturbance, are reflected in our method. We have proved that the estimation error of this method is bounded. Furthermore, the bound on the Euclidean norm of the estimation error is derived. The simulation results demonstrate that this method can provide accurate estimates of time‐varying parameters even under the influence of bounded disturbance. Copyright © 2010 John Wiley & Sons, Ltd.