2.50
Hdl Handle:
http://hdl.handle.net/10547/275837
Title:
Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems
Authors:
Hou, Zhongsheng; Jin, Shangtai
Abstract:
In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.
Affiliation:
Beijing Jiaotong University, Beijing, China
Citation:
Hou, |Z., Jin, S. (2011) 'Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems' IEEE Transactions on Neural Networks 22 (12):2173-2188
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Journal:
IEEE Transactions on Neural Networks
Issue Date:
2011
URI:
http://hdl.handle.net/10547/275837
DOI:
10.1109/TNN.2011.2176141
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6093751
Type:
Article
Language:
en
ISSN:
1045-9227; 1941-0093
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorHou, Zhongshengen_GB
dc.contributor.authorJin, Shangtaien_GB
dc.date.accessioned2013-03-25T13:23:24Z-
dc.date.available2013-03-25T13:23:24Z-
dc.date.issued2011-
dc.identifier.citationHou, |Z., Jin, S. (2011) 'Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems' IEEE Transactions on Neural Networks 22 (12):2173-2188en_GB
dc.identifier.issn1045-9227-
dc.identifier.issn1941-0093-
dc.identifier.doi10.1109/TNN.2011.2176141-
dc.identifier.urihttp://hdl.handle.net/10547/275837-
dc.description.abstractIn this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.en_GB
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6093751en_GB
dc.rightsArchived with thanks to IEEE Transactions on Neural Networksen_GB
dc.subjectadaptive controlen_GB
dc.subjectdiscrete time systemsen_GB
dc.subjectMIMOen_GB
dc.titleData-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systemsen
dc.typeArticleen
dc.contributor.departmentBeijing Jiaotong University, Beijing, Chinaen_GB
dc.identifier.journalIEEE Transactions on Neural Networksen_GB
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