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Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918764317

Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

About this item

Full title

Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

Publisher

West Yorkshire: Science and Information (SAI) Organization Limited

Journal title

International journal of advanced computer science & applications, 2023, Vol.14 (12)

Language

English

Formats

Publication information

Publisher

West Yorkshire: Science and Information (SAI) Organization Limited

More information

Scope and Contents

Contents

In this paper, an iterative learning control (ILC) strategy under compression mapping framework is presented for high relative degree discrete-time systems with random initial shifts. Firstly, utilizing the high relative degree of the system and difference term, a control law is designed and a p-order non-homogeneous linear difference equation is e...

Alternative Titles

Full title

Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2918764317

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918764317

Other Identifiers

ISSN

2158-107X

E-ISSN

2156-5570

DOI

10.14569/IJACSA.2023.0141295

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