Fusion of hard and soft control techniques for prosthetic hand

Cheng Hung Chen, D. Subbaram Naidu, Alba Perez, Marco P. Schoen

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

10 Scopus citations

Abstract

Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate these deficiencies, by allowing for reduced computational loads and the ability to find global optimal solutions, even for complex cost surfaces. This paper presents fusion of soft computing or control technique of genetic algorithm (GA) and hard computing technique of proportional integral derivative (PID) control with application to prosthetic hand. An adaptive neuro-fuzzy inference system (ANFIS) is used for inverse kinematics of the three-link index finger, and feedback linearization is used for the dynamics of the hand and the GA is used to find the optimal parameters of the PID controller. Simulation results with practical data shows good results for the prosthetic hand to hold a square object with a two-link thumb and index finger.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th IASTED International Conference on Intelligent Systems and Control, ISC 2008
Pages120-125
Number of pages6
StatePublished - Dec 1 2008
Event11th IASTED International Conference on Intelligent Systems and Control, ISC 2008 - Orlando, FL, United States
Duration: Nov 16 2008Nov 18 2008

Publication series

NameProceedings of the IASTED International Conference on Intelligent Systems and Control
ISSN (Print)1025-8973

Other

Other11th IASTED International Conference on Intelligent Systems and Control, ISC 2008
CountryUnited States
CityOrlando, FL
Period11/16/0811/18/08

Keywords

  • Adaptive neuro-fuzzy inference system
  • Computational intelligence
  • Genetic algorithm
  • PID controller
  • Prosthetic hand

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