Hybrid control strategies for a five-finger robotic hand

Cheng Hung Chen, D. Subbaram Naidu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This paper presents a hybrid controller of soft control techniques, adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL), and hard control technique, proportional-derivative (PD), for a five-finger robotic hand with 14-degrees-of-freedom (DoF). The ANFIS is used for inverse kinematics of three-link fingers and FL is used for tuning the PD parameters with 2 input layers (error and error rate) using 7 triangular membership functions and 49 fuzzy logic rules. Simulation results with the hybrid of FL-tuned PD controller exhibit superior performance compared to PD, PID and FL controllers alone.

Original languageEnglish (US)
Pages (from-to)382-390
Number of pages9
JournalBiomedical Signal Processing and Control
Volume8
Issue number4
DOIs
StatePublished - Jul 2013

Bibliographical note

Funding Information:
The research was sponsored by the U.S. Department of the Army , under the award number W81XWH-10-1-0128 awarded and administered by the U.S. Army Medical Research Acquisition Activity, 820 Chandler Street, Fort Detrick, MD 21702-5014, USA. The information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. For purposes of this article, information includes news releases, articles, manuscripts, brochures, advertisements, still and motion pictures, speeches, trade association proceedings, etc. We appreciate the reviewer's comments improving this work.

Keywords

  • Adaptive neuro-fuzzy inference system
  • Fuzzy logic
  • Hybrid control
  • PD control
  • Prosthetic hand
  • Robotic hand
  • Soft computing

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