A Multiobjective Evolutionary Neuro-Controller for Nonminimum Phase Systems(Biocybernetics, Neurocomputing)
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概要
- 論文の詳細を見る
Nonminimum phase systems are difficult to be controlled with a conventional PID-type controller because of their inherent characteristics of undershooting. A neuro-contrailer combined with a PID-type controller has been shown to improve the control performance of the nonminimum phase systems while maintaining stability. In this paper, we apply a multiobjective evolutionary optimization method for training the neurocontroller to reduce the undershooting of the nonminimum phase system. The computer simulation shows that the proposed multiobjective approach is very effective and suitable because it can minimize the control error as well as reduce undershooting and chattering. This method can be applied to many industrial nonminimum phase problems with ease.
- 社団法人電子情報通信学会の論文
- 2004-11-01
著者
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PARK Cheol
Department of Diagnostic Pathology, Samsung Medical Center, Sungkyunkwan University School of Medici
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Lee Hajoon
Department Of Electrical Engineering And Computer Science
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Park C
Department Of Electrical Engineering And Computer Science
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NAM Dongkyung
Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and T
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PARK Sangbong
Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and T
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PARK Lae-Jeong
School of Electronics Engineering and Information Technology, Kangnung National University
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Park Cheol
Department Of Diagnostic Pathology Samsung Medical Center Sungkyunkwan University School Of Medicine
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Nam Dongkyung
Department Of Electrical Engineering And Computer Science
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Park Lae-jeong
School Of Electronics Engineering And Information Technology Kangnung National University
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Lee H
Department Of Electrical Engineering And Computer Science
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Park Sangbong
Department Of Electrical Engineering And Computer Science Korea Advanced Institute Of Science And Te
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