EVENT-BASED INTELLIGENT CONTROL USING ENDOMORPHIC NEURAL-NETWORK MODEL

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In event-based control, a controller checks the responses of sensors about commands with time constraints. To do this, the event-based controller should have some information about the dynamics of the plant at discrete levels, its desired state transitions, and inputs to move the state transitions. In an existing modelling method, the information is represented by a tabular form, which is not adaptable to the variation of set positions. An artificial neural network was taken as a new modelling method to solve this problem. Experiments show that this neural network model works well in the dynamic variation of set positions. This endomorphic neural network modelling helps us to construct a more autonomous event-based controller.
Publisher
TAYLOR FRANCIS
Issue Date
1995
Language
English
Article Type
Article
Keywords

SYSTEMS

Citation

APPLIED ARTIFICIAL INTELLIGENCE, v.9, no.5, pp.479 - 494

ISSN
0883-9514
URI
http://hdl.handle.net/10203/22888
Appears in Collection
EE-Journal Papers(저널논문)
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