Hybrid control strategy for five-fingered smart prosthetic hand

G. Hung Chen, Desineni S Naidu, Alba Perez-Gracia, Marco P. Schoen

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

8 Scopus citations

Abstract

This paper presents a hybrid of soft computing or control technique of adaptive neuro-fuzzy inference system (ANFIS) and hard computing or control technique of finite-time linear quadratic optimal control for the 14 degrees of freedom (DOFs), five-fingered smart prosthetic hand. In particular, ANFIS is used for inverse kinematics, and the optimal control is used for feedback linearized dynamics to minimize tracking error. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller showed enhanced performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Pages5102-5107
Number of pages6
DOIs
StatePublished - Dec 1 2009
Externally publishedYes
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
CountryChina
CityShanghai
Period12/15/0912/18/09

Keywords

  • Adaptive neuro-fuzzy inference system
  • Hybrid control
  • Optimal control
  • PID control
  • Prosthetic hand

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  • Cite this

    Chen, G. H., Naidu, D. S., Perez-Gracia, A., & Schoen, M. P. (2009). Hybrid control strategy for five-fingered smart prosthetic hand. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 (pp. 5102-5107). [5400771] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2009.5400771