A servo system control with time-varying and nonlinear load conditions using type-2 TSK fuzzy neural system
作者： Erdal Kayacan , Yesim Oniz , Ayse Cisel Aras , Okyay Kaynak , Rahib Abiyev
DOI: 10.1016/J.ASOC.2011.03.008
关键词:
摘要: Abstract: A type-2 Takagi-Sugeno-Kang fuzzy neural system is proposed and its parameter update rules are derived using clustering gradient learning algorithms. The used for the control identification of a real-time servo system. Fuzzy c-means algorithm to determine initial places membership functions ensure that descent afterwards converges in shorter time. number different load conditions including nonlinear time-varying ones investigate performance algorithm. structure has ability regulate with reduced oscillations when compared results type-1 counterpart around set point signal presence disturbances.
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