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Analysis and applications of the motion message estimator for network control systems
Author(s) -
Hsieh ChenChou,
Hsu PauLo
Publication year - 2008
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.5
Subject(s) - dropout (neural networks) , estimator , computer science , feed forward , networked control system , construct (python library) , motion control , control system , control (management) , control theory (sociology) , bandwidth (computing) , control engineering , engineering , artificial intelligence , computer network , mathematics , machine learning , statistics , electrical engineering , robot
The time‐delay effect in network systems is unavoidable because of its limited transmission bandwidth. In real‐time network control systems (NCS), all messages are required to be transmitted or received to meet specifications of the deadline. Therefore, the data dropout may thus occur in NCS due to its time delay in a stochastic nature. In this paper, a motion message estimator is proposed to construct a real‐time motion NCS to significantly reduce the data‐dropout effect. Both simulation and experimental results indicate that a 3rd‐order message estimator based on the Taylor expansion can be properly implemented in NCS for industrial motion control systems. Furthermore, since the uncertainties of the NCS estimator are greatly suppressed by applying the message, experimental results indicate that its integration with the feedforward control leads to significantly improved accuracy for the NCS implemented on an industrial computerized numerical control (CNC) machine tool. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society