NDLI: Extremum seeking control for systems with time-varying extremum

Content Provider	IEEE Xplore Digital Library
Author	Sahneh, F.D. Guoqiang Hu Lihua Xie
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA (Sahneh, F.D.) \|\| EXQUISITUS, Centre for E-City, School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore 639798 (Guoqiang Hu; Lihua Xie)
Abstract	Most extremum seeking control methods consider time-independent input-to-output mappings. Correspondingly, these methods are suitable for systems where the variations of the mapping are much slower than the adaptation dynamics. The few existing results for the case where the mapping is time-dependent require the knowledge of the structure of the time-dependency. In this paper, an extremum seeking algorithm is proposed for mappings where the optimal point is time-varying. The time variations are considered to be of a general form. The proposed extremum seeking control method basically consists of two separate components, i.e., 1) real-time gradient estimation and 2) gradient search for tracking a time-varying optimal point. The gradient is estimated by adding a sinusoidal perturbation to the searching signal and then demodulating the measured output. The estimated gradient signal is then fed into a novel gradient search method, which is proven to move the searching signal toward the optimal value.
Starting Page	225
Ending Page	231
File Size	357530
Page Count	7
File Format	PDF
ISBN	9781467325813
ISSN	21612927
e-ISBN	9789881563811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	tracking control Extremum seeking gradient estimation optimization Estimation gradient search Search problems Educational institutions Robustness Stability analysis Real-time systems
Content Type	Text
Resource Type	Article

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