Infinite-Mode networks for motion control

Baris Yalcin, Kouhei Ohnishi

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In this paper, a novel multiple-input-multiple-output network model entitled "infinite-mode networks" (IMNs) is explained. The model proposes a new and challenging design concept. It is a dual structure and combines neural networks (NNs) to linear models. It has mathematically clear input-output relationship as compared to NNs. The model has a desired embedded internal function, which roughly determines a route for the whole system to follow as DNA does for biological systems. By this model, infinitely many error dimensions can be defined, and each error converges to zero in a stable manner. The network outputs include logical combinations of infinite modes of reference states, which consequently result in a substantial improvement of the control system performance. In order to support the network theory, time-delay and noise-suppression experiments on a four-channel haptic bilateral teleoperation control system are analyzed. An analysis between NNs, sliding-mode NNs, and IMNs is introduced. Possible future applications of IMNs are discussed.

Original languageEnglish
Pages (from-to)2933-2944
Number of pages12
JournalIEEE Transactions on Industrial Electronics
Volume56
Issue number8
DOIs
Publication statusPublished - 2009

Fingerprint

Motion control
Neural networks
Control systems
Circuit theory
Biological systems
Remote control
Time delay
DNA
Experiments

Keywords

  • Artificial intelligence
  • Haptics
  • Infinite-mode networks (IMNs)
  • Motion control
  • Neural networks (NNs)
  • Noise suppression
  • teleoperation
  • Time delay

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Infinite-Mode networks for motion control. / Yalcin, Baris; Ohnishi, Kouhei.

In: IEEE Transactions on Industrial Electronics, Vol. 56, No. 8, 2009, p. 2933-2944.

Research output: Contribution to journalArticle

Yalcin, Baris ; Ohnishi, Kouhei. / Infinite-Mode networks for motion control. In: IEEE Transactions on Industrial Electronics. 2009 ; Vol. 56, No. 8. pp. 2933-2944.
@article{7637192516fd41eb940e2078a74070a4,
title = "Infinite-Mode networks for motion control",
abstract = "In this paper, a novel multiple-input-multiple-output network model entitled {"}infinite-mode networks{"} (IMNs) is explained. The model proposes a new and challenging design concept. It is a dual structure and combines neural networks (NNs) to linear models. It has mathematically clear input-output relationship as compared to NNs. The model has a desired embedded internal function, which roughly determines a route for the whole system to follow as DNA does for biological systems. By this model, infinitely many error dimensions can be defined, and each error converges to zero in a stable manner. The network outputs include logical combinations of infinite modes of reference states, which consequently result in a substantial improvement of the control system performance. In order to support the network theory, time-delay and noise-suppression experiments on a four-channel haptic bilateral teleoperation control system are analyzed. An analysis between NNs, sliding-mode NNs, and IMNs is introduced. Possible future applications of IMNs are discussed.",
keywords = "Artificial intelligence, Haptics, Infinite-mode networks (IMNs), Motion control, Neural networks (NNs), Noise suppression, teleoperation, Time delay",
author = "Baris Yalcin and Kouhei Ohnishi",
year = "2009",
doi = "10.1109/TIE.2009.2024096",
language = "English",
volume = "56",
pages = "2933--2944",
journal = "IEEE Transactions on Industrial Electronics",
issn = "0278-0046",
publisher = "IEEE Industrial Electronics Society",
number = "8",

}

TY - JOUR

T1 - Infinite-Mode networks for motion control

AU - Yalcin, Baris

AU - Ohnishi, Kouhei

PY - 2009

Y1 - 2009

N2 - In this paper, a novel multiple-input-multiple-output network model entitled "infinite-mode networks" (IMNs) is explained. The model proposes a new and challenging design concept. It is a dual structure and combines neural networks (NNs) to linear models. It has mathematically clear input-output relationship as compared to NNs. The model has a desired embedded internal function, which roughly determines a route for the whole system to follow as DNA does for biological systems. By this model, infinitely many error dimensions can be defined, and each error converges to zero in a stable manner. The network outputs include logical combinations of infinite modes of reference states, which consequently result in a substantial improvement of the control system performance. In order to support the network theory, time-delay and noise-suppression experiments on a four-channel haptic bilateral teleoperation control system are analyzed. An analysis between NNs, sliding-mode NNs, and IMNs is introduced. Possible future applications of IMNs are discussed.

AB - In this paper, a novel multiple-input-multiple-output network model entitled "infinite-mode networks" (IMNs) is explained. The model proposes a new and challenging design concept. It is a dual structure and combines neural networks (NNs) to linear models. It has mathematically clear input-output relationship as compared to NNs. The model has a desired embedded internal function, which roughly determines a route for the whole system to follow as DNA does for biological systems. By this model, infinitely many error dimensions can be defined, and each error converges to zero in a stable manner. The network outputs include logical combinations of infinite modes of reference states, which consequently result in a substantial improvement of the control system performance. In order to support the network theory, time-delay and noise-suppression experiments on a four-channel haptic bilateral teleoperation control system are analyzed. An analysis between NNs, sliding-mode NNs, and IMNs is introduced. Possible future applications of IMNs are discussed.

KW - Artificial intelligence

KW - Haptics

KW - Infinite-mode networks (IMNs)

KW - Motion control

KW - Neural networks (NNs)

KW - Noise suppression

KW - teleoperation

KW - Time delay

UR - http://www.scopus.com/inward/record.url?scp=68449092482&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=68449092482&partnerID=8YFLogxK

U2 - 10.1109/TIE.2009.2024096

DO - 10.1109/TIE.2009.2024096

M3 - Article

AN - SCOPUS:68449092482

VL - 56

SP - 2933

EP - 2944

JO - IEEE Transactions on Industrial Electronics

JF - IEEE Transactions on Industrial Electronics

SN - 0278-0046

IS - 8

ER -