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EEG-Based Driver Drowsiness Estimation Using an Online Multi-View and Transfer TSK Fuzzy System

IEEE transactions on intelligent transportation systems (Print), 2021
In the field of intelligent transportation, transfer learning (TL) is often used to recognize EEG-based drowsy driving for a new subject with few subject-specific calibration data.
Yizhang Jiang   +4 more
semanticscholar   +1 more source

Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system

Information Sciences, 2021
In this study, the control problem of complex robot system with uncertainties and disturbances is addressed. Fuzzy system-fuzzy neural network-backstepping control (FS-FNN-BSC) system is proposed, which can guarantee the accurate, stable and efficient ...
Kunming Zheng   +3 more
semanticscholar   +1 more source

Command Filter-Based Adaptive Fuzzy Finite-Time Output Feedback Control of Nonlinear Electrohydraulic Servo System

IEEE Transactions on Instrumentation and Measurement, 2022
In this article, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for the electrohydraulic servo system.
Jiafeng Li   +4 more
semanticscholar   +1 more source

Stabilization of T-S Fuzzy System With Time Delay Under Sampled-Data Control Using a New Looped-Functional

IEEE transactions on fuzzy systems, 2020
This paper investigates the sampled-data stabilization problem for a Takagi–Sugeno (T-S) fuzzy system with time delay. By taking the information of states within the intervals from $t_{k}$ to $t$ and $t$ to $t_{k+1}$ into account, a new two-side delay ...
C. Hua, Shuangshuang Wu, X. Guan
semanticscholar   +1 more source

Fuzzy systems

Soft Computing, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
James Buckley, Leonard Jowers
  +5 more sources

An Interval Type-3 Fuzzy System and a New Online Fractional-Order Learning Algorithm: Theory and Practice

IEEE transactions on fuzzy systems, 2020
The main reason of the extensive usage of the fuzzy systems in many branches of science is their approximation ability. In this paper, an interval type-3 fuzzy system (IT3FS) is proposed.
A. Mohammadzadeh   +2 more
semanticscholar   +1 more source

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