NDLI: Learning identification of time varying parameters in nonlinear systems with initial state learning

Content Provider	IEEE Xplore Digital Library
Author	Cao Wei Sun Ming Wang Yan-wei
Copyright Year	2013
Description	Author affiliation: Coll. of Autom., Harbin Eng. Univ., Harbin, China (Wang Yan-wei) \|\| Coll. of Comput. & Control Eng., Qiqihar Univ., Qiqihar, China (Cao Wei; Sun Ming)
Abstract	For a class of nonlinear systems with unknown time varying parameters, a iterative learning identification method with initial state learning is proposed. The method uses the operator theory to prove that the output of identification can track the expected trajectory completely after the iterative learn of system under the arbitrary initial state, and provides the sufficient convergent condition by the spectral radius form of the method. This method not only can realize the complete identification of nonlinear systems' unknown time varying parameters in finite time horizon, but also can solve the problem that the iterative learning identification needs the rigid repetition of initial state. Simulation results verify the validity of the proposed method.
Starting Page	2868
Ending Page	2872
File Size	256045
Page Count	5
File Format	PDF
ISBN	9789881563835
ISSN	19341768
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	TCCT, CAA
Subject Keyword	Adaptive systems Control engineering Automation time varying parameters Educational institutions iterative learning identification Electronic mail nonlinear system Nonlinear systems operator theory Time-varying systems
Content Type	Text
Resource Type	Article

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