Neural Network based adaptive control of a flexible link manipulator

Niaz Mahmmood, Bruce L. Walcott

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

This paper presents a design methodology for an on-line self-turning adaptive control (OLSTAC) of a single flexible link manipulator (FLM) using back-propagation neural networks (BPNN). The particular problem discussed is the on-line system identification of a FLM using BPNN and the OLSTAC of a FLM using a separate neural network as a controller. A finite-element model of a FLM is obtained using ANSYS. The pseudo-link concepts developed in are used to determine on-line angular displacement of the end effector of the FLM. The illustrative simulation results are promising and show that the OLSTAC technique can be applied to flexible structures such as a FLM resulting reduced error and increased robustness.

Original languageEnglish
Pages851-857
Number of pages7
StatePublished - 1993
EventProceedings of the IEEE 1993 National Aerospace and Electronics Conference - Dayton, OH, USA
Duration: May 24 1993May 28 1993

Conference

ConferenceProceedings of the IEEE 1993 National Aerospace and Electronics Conference
CityDayton, OH, USA
Period5/24/935/28/93

ASJC Scopus subject areas

  • General Engineering

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