Multiple Model ILC for Continuous-Time Nonlinear Systems

Joint Authors

Li, Xiao-Li
Wang, Kang
Li, Yang

Source

Abstract and Applied Analysis

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

Mathematics

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