Sliding mode control theory-based algorithm for online learning in type-2 fuzzy neural networks: application to velocity control of an electro hydraulic servo system

DOI10.1002/acs.1292zbMath1250.93041OpenAlexW1910484443MaRDI QIDQ2912300

Erdal Kayacan, Okyay Kaynak

Publication date: 14 September 2012

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.1292

zbMATH Keywords

sliding mode controltype-2 fuzzy logic systemselectro hydraulic servo systemtype-2 fuzzy neuro systems

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Application models in control theory (93C95) Variable structure systems (93B12)

Related Items (6)

Special issue on ‘new results on neuro-fuzzy adaptive control systems’ ⋮ Forecasting by TSK general type‐2 fuzzy logic systems optimized with genetic algorithms ⋮ A new interval type-2 fuzzy controller for stabilization of interval type-2 T-S fuzzy systems ⋮ A review on interval type-2 fuzzy logic applications in intelligent control ⋮ Dissipative control of interval type-2 nonhomogeneous Markovian jump fuzzy systems with incomplete transition descriptions ⋮ Accuracy and complexity evaluation of defuzzification strategies for the discretised interval type-2 fuzzy set

Cites Work

• Toward extended fuzzy logic -- a first step
• Extended fuzzy function model with stable learning methods for online system identification
• A genetic-based neuro-fuzzy controller for blind equalization of time-varying channels

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