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An identification method for MIMO continuous‐time systems via iterative learning control concepts
Author(s) -
Sakai Fumitoshi,
Sugie Toshiharu
Publication year - 2011
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.265
Subject(s) - iterative learning control , multivariable calculus , robustness (evolution) , control theory (sociology) , identification (biology) , mimo , projection (relational algebra) , noise (video) , computer science , system identification , iterative method , algorithm , control (management) , control engineering , artificial intelligence , engineering , data modeling , computer network , biochemistry , chemistry , botany , channel (broadcasting) , image (mathematics) , gene , database , biology
This paper presents an identification method based on an iterative learning control (ILC) concept for the multivariable continuous‐time system. For this purpose a projection type ILC, which updates the input in an appropriate parameter space, is extended to the case of multivariable systems. The robustness against measurement noise is achieved through both projection of continuous‐time I/O signals onto a finite dimensional space and noise tolerant learning algorithms. Finally, a numerical example is given to demonstrate how the parameter estimation can be achieved through the proposed identification method in the presence of heavy measurement noises. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society