![](/images/graphics-bg.png)
Multiple Model ILC for Continuous-Time Nonlinear Systems
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-10-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Multiple model iterative learning control (MMILC) method is proposed to deal with the continuous-time nonlinear system with uncertain and iteration-varying parameters.
In this kind of control strategy, multiple models are established to cover the uncertainty of system; a switching mechanism is used to decide the most appropriate model for system in current iteration.
For system operating iteratively in a fixed time interval with uncertain or jumping parameters, this kind of MMILC can improve the transient response and control property greatly.
Asymptotical convergence is demonstrated theoretically, and the control effectivenessis illustrated by numerical simulation.
American Psychological Association (APA)
Li, Xiao-Li& Wang, Kang& Li, Yang. 2014. Multiple Model ILC for Continuous-Time Nonlinear Systems. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1034151
Modern Language Association (MLA)
Li, Xiao-Li…[et al.]. Multiple Model ILC for Continuous-Time Nonlinear Systems. Abstract and Applied Analysis No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1034151
American Medical Association (AMA)
Li, Xiao-Li& Wang, Kang& Li, Yang. Multiple Model ILC for Continuous-Time Nonlinear Systems. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1034151
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034151