On the Tensor Product based qLPV modeling of bio-inspired dynamic processes

Peter Galambos, Jozsef Kuti, Peter Baranyi

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

1 Citation (Scopus)

Abstract

A recently published definition of Cognitive Control draws twofold sense to characterize the main point of this new scientific field. On the one hand, Cognitive Control aims to apply the results of control theory to regulate natural or artificial cognitive systems. On the other hand it points toward the modeling of cognitive processes of different levels utilizing the apparatus of the modern systems theory. This paper discusses a systematic way based on the Tensor Product (TP) model transformation of deriving the qLPV model of complex dynamic processes such as balancing that are inherent capability of every vertebrates.

Original languageEnglish
Title of host publicationINES 2013 - IEEE 17th International Conference on Intelligent Engineering Systems, Proceedings
Pages79-84
Number of pages6
DOIs
Publication statusPublished - Dec 12 2013
Event17th IEEE International Conference on Intelligent Engineering Systems, INES 2013 - San Jose, Costa Rica
Duration: Jun 19 2013Jun 21 2013

Publication series

NameINES 2013 - IEEE 17th International Conference on Intelligent Engineering Systems, Proceedings

Other

Other17th IEEE International Conference on Intelligent Engineering Systems, INES 2013
CountryCosta Rica
CitySan Jose
Period6/19/136/21/13

Keywords

  • Cognitive Control
  • TP model transformation
  • balancing
  • inverted pendulum
  • qLPV modeling
  • tightrope walking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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  • Cite this

    Galambos, P., Kuti, J., & Baranyi, P. (2013). On the Tensor Product based qLPV modeling of bio-inspired dynamic processes. In INES 2013 - IEEE 17th International Conference on Intelligent Engineering Systems, Proceedings (pp. 79-84). [6632787] (INES 2013 - IEEE 17th International Conference on Intelligent Engineering Systems, Proceedings). https://doi.org/10.1109/INES.2013.6632787