Infinite-Mode networks for motion control

Baris Yalcin, Kouhei Ohnishi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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
Issue number8
Publication statusPublished - 2009
Externally publishedYes


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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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