Adaptive Feedforward Control of Cydic Movements Using Artificial Neural Networks

James J. Abbas, Howard J. Chizeck

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

2 Scopus citations

Abstract

An adaptive neural network control system has been designed for the purpose of controlling cyclic movements of nonlinear dynamic systems with input time delays. The work is part of a larger project directed at the development of Functional Neuromuscular Stimulation (FNS) systems for restoring the ability to stand and to walk to people with paralysis of lower extremity musculature. The adaptive feedforward (FF) controller is implemented as a two-stage neural network. The first stage, the pattern generator (PG), generates a cyclic pattern of activity. The signals from the PG are additively filtered by the second stage, the pattern shaper (PS). This stage uses modifications to standard artificial neural network learning algorithms to adapt its filter properties. The control system has been evaluated in computer simulation on a musculoskeletal model which consisted of two muscles acting on a swinging pendulum. The control system was demonstrated to provide automated customization of the FF controller parameters for a given musculoskeletal system as well as on-line adaptation of the FF controller parameters to account for changes in the musculoskeletal system. This addictive feedforward control strategy may be impropriate for other applications in the control of nonlinear dynamic systems with input time delays.

Original languageEnglish (US)
Title of host publicationProceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages832-837
Number of pages6
ISBN (Electronic)0780305590
DOIs
StatePublished - 1992
Event1992 International Joint Conference on Neural Networks, IJCNN 1992 - Baltimore, United States
Duration: Jun 7 1992Jun 11 1992

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2

Conference

Conference1992 International Joint Conference on Neural Networks, IJCNN 1992
Country/TerritoryUnited States
CityBaltimore
Period6/7/926/11/92

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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