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Controller scheduling using neural networks: Implementation and experimental results

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents the results of simulation and control experiments using a recently proposed method for real-time switching among a pool of controllers. The switching strategy selects the current controller based on neural network estimates of the future system performance for each controller. This neural-network-based switching controller has been implemented for a simulated inverted pendulum and a level control system for an underwater vehicle in our laboratory. The objectives of the experiments presented here are to demonstrate the feasibility of this approach to switching control for real systems and to identify techniques to deal with practical issues that arise in the training of the neural networks and the real-time switching behavior of the system. This experimental work complements on-going theoretical investigations of the method which will be reported elsewhere.

Original languageEnglish
Title of host publicationHybrid Systems V
EditorsPanos Antsaklis, Michael Lemmon, Wolf Kohn, Anil Nerode, Shankar Sastry
PublisherSpringer Verlag
Pages86-99
Number of pages14
ISBN (Print)354065643X, 9783540656432
DOIs
StatePublished - 1999
Externally publishedYes
Event5th International Hybrid Systems Workshop, 1997 - Notre Dame, United States
Duration: 11 Sep 199713 Sep 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1567
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Hybrid Systems Workshop, 1997
Country/TerritoryUnited States
CityNotre Dame
Period11/09/9713/09/97

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