Application of infinite mode networks theory to haptic teleoperation for noise suppression

Baris Yalcin, Kouhei Ohnishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, a novel multi input multi output network model entitled as "infinite mode networks" is explained. The model proposes a new and challenging design concept. It has mathematically clear input output relationship compared to neural networks. This new 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. Additional to the network theory, applications on a four channel haptic bilateral teleoperation control system whose performance is degraded via feedback and feedforward sensor noise are shown. This type of noise suppression is challenging because of two reasons: to obtain an ideal performance disturbance observers necessitate high gains that in turn make the system unstable under feedback and feedforward noises, in a four channel structure noise is reflected back and forth to both bilateral robots which in turn results in unpurified force and position data.

Original languageEnglish
Title of host publicationProceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008
Pages1845-1850
Number of pages6
DOIs
Publication statusPublished - 2008
Event34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008 - Orlando, FL, United States
Duration: 2008 Nov 102008 Nov 13

Other

Other34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008
CountryUnited States
CityOrlando, FL
Period08/11/1008/11/13

Fingerprint

Circuit theory
Remote control
Feedback
Biological systems
DNA
Robots
Neural networks
Control systems
Sensors

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Yalcin, B., & Ohnishi, K. (2008). Application of infinite mode networks theory to haptic teleoperation for noise suppression. In Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008 (pp. 1845-1850). [4758236] https://doi.org/10.1109/IECON.2008.4758236

Application of infinite mode networks theory to haptic teleoperation for noise suppression. / Yalcin, Baris; Ohnishi, Kouhei.

Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008. 2008. p. 1845-1850 4758236.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yalcin, B & Ohnishi, K 2008, Application of infinite mode networks theory to haptic teleoperation for noise suppression. in Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008., 4758236, pp. 1845-1850, 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008, Orlando, FL, United States, 08/11/10. https://doi.org/10.1109/IECON.2008.4758236
Yalcin B, Ohnishi K. Application of infinite mode networks theory to haptic teleoperation for noise suppression. In Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008. 2008. p. 1845-1850. 4758236 https://doi.org/10.1109/IECON.2008.4758236
Yalcin, Baris ; Ohnishi, Kouhei. / Application of infinite mode networks theory to haptic teleoperation for noise suppression. Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008. 2008. pp. 1845-1850
@inproceedings{70bca77667bf480baa7f78a70fb31bd2,
title = "Application of infinite mode networks theory to haptic teleoperation for noise suppression",
abstract = "In this paper, a novel multi input multi output network model entitled as {"}infinite mode networks{"} is explained. The model proposes a new and challenging design concept. It has mathematically clear input output relationship compared to neural networks. This new 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. Additional to the network theory, applications on a four channel haptic bilateral teleoperation control system whose performance is degraded via feedback and feedforward sensor noise are shown. This type of noise suppression is challenging because of two reasons: to obtain an ideal performance disturbance observers necessitate high gains that in turn make the system unstable under feedback and feedforward noises, in a four channel structure noise is reflected back and forth to both bilateral robots which in turn results in unpurified force and position data.",
author = "Baris Yalcin and Kouhei Ohnishi",
year = "2008",
doi = "10.1109/IECON.2008.4758236",
language = "English",
isbn = "9781424417667",
pages = "1845--1850",
booktitle = "Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008",

}

TY - GEN

T1 - Application of infinite mode networks theory to haptic teleoperation for noise suppression

AU - Yalcin, Baris

AU - Ohnishi, Kouhei

PY - 2008

Y1 - 2008

N2 - In this paper, a novel multi input multi output network model entitled as "infinite mode networks" is explained. The model proposes a new and challenging design concept. It has mathematically clear input output relationship compared to neural networks. This new 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. Additional to the network theory, applications on a four channel haptic bilateral teleoperation control system whose performance is degraded via feedback and feedforward sensor noise are shown. This type of noise suppression is challenging because of two reasons: to obtain an ideal performance disturbance observers necessitate high gains that in turn make the system unstable under feedback and feedforward noises, in a four channel structure noise is reflected back and forth to both bilateral robots which in turn results in unpurified force and position data.

AB - In this paper, a novel multi input multi output network model entitled as "infinite mode networks" is explained. The model proposes a new and challenging design concept. It has mathematically clear input output relationship compared to neural networks. This new 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. Additional to the network theory, applications on a four channel haptic bilateral teleoperation control system whose performance is degraded via feedback and feedforward sensor noise are shown. This type of noise suppression is challenging because of two reasons: to obtain an ideal performance disturbance observers necessitate high gains that in turn make the system unstable under feedback and feedforward noises, in a four channel structure noise is reflected back and forth to both bilateral robots which in turn results in unpurified force and position data.

UR - http://www.scopus.com/inward/record.url?scp=63149176547&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=63149176547&partnerID=8YFLogxK

U2 - 10.1109/IECON.2008.4758236

DO - 10.1109/IECON.2008.4758236

M3 - Conference contribution

AN - SCOPUS:63149176547

SN - 9781424417667

SP - 1845

EP - 1850

BT - Proceedings - 34th Annual Conference of the IEEE Industrial Electronics Society, IECON 2008

ER -