Open AccessNeural Network-Based Speed Control of A Two-Mass-Model System
Author(s) -
Rached Dhaouadi,
Ecole Polytechnique de Tunisie,
Khaled Nouri
Publication year - 1999
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1883-8014
pISSN - 1343-0130
DOI - 10.20965/jaciii.1999.p0427
Subject(s) - computer science , artificial neural network , scheme (mathematics) , control theory (sociology) , inverse , inverse system , control system , inverse dynamics , artificial intelligence , control (management) , kinematics , mathematics , engineering , electrical engineering , classical mechanics , physics , mathematical analysis , geometry
We present an application of artificial neural networks to the problem of controlling the speed of an elastic drive system. We derive a neural network structure to simulate the inverse dynamics of the system, then implement the direct inverse control scheme in a closed loop. The neural network learning is done on-line to adaptively control the speed to follow a stepwise changing reference. The experimental results with a two-mass-model analog board confirm the effectiveness of the proposed neurocontrol scheme.
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