Supervisory adaptive tracking control of robot manipulators using interval type-2 TSK fuzzy logic system

IET Control Theory and Applications ◽

10.1049/iet-cta.2010.0703 ◽

2011 ◽

Vol 5 (15) ◽

pp. 1796-1807 ◽

Author(s):

C.-S. Chen

Keyword(s):

Fuzzy Logic ◽

Tracking Control ◽

Robot Manipulators ◽

Fuzzy Logic System ◽

Adaptive Tracking Control ◽

Adaptive Tracking ◽

Interval Type ◽

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Robust Adaptive Tracking Control for Hypersonic Vehicle Based on Interval Type-2 Fuzzy Logic System and Small-Gain Approach

IEEE Transactions on Cybernetics ◽

10.1109/tcyb.2019.2927309 ◽

2019 ◽

pp. 1-14 ◽

Author(s):

Xinlong Tao ◽

Jianqiang Yi ◽

Zhiqiang Pu ◽

Tianyi Xiong

Keyword(s):

Fuzzy Logic ◽

Tracking Control ◽

Fuzzy Logic System ◽

Hypersonic Vehicle ◽

Adaptive Tracking Control ◽

Robust Adaptive ◽

Interval Type ◽

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Fault tolerant trajectory tracking control design for interval-type-2 Takagi-Sugeno fuzzy logic system

International Journal of Modelling Identification and Control ◽

10.1504/ijmic.2017.083786 ◽

2017 ◽

Vol 27 (3) ◽

pp. 230 ◽

Author(s):

Imen Maalej ◽

Chokri Rekik ◽

Donia Ben Halima Abid

Keyword(s):

Fuzzy Logic ◽

Tracking Control ◽

Fault Tolerant ◽

Control Design ◽

Fuzzy Logic System ◽

Trajectory Tracking Control ◽

Interval Type ◽

Takagi Sugeno ◽

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A New Interval Type-2 Fuzzy Logic System Under Dynamic Environment: Application to Financial Investment

SSRN Electronic Journal ◽

10.2139/ssrn.3532096 ◽

2020 ◽

Author(s):

Akihiko Takahashi ◽

Soichiro Takahashi

Keyword(s):

Fuzzy Logic ◽

Dynamic Environment ◽

Fuzzy Logic System ◽

Financial Investment ◽

Interval Type ◽

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A new interval type-2 fuzzy logic system under dynamic environment: Application to financial investment

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2021.104154 ◽

2021 ◽

Vol 100 ◽

pp. 104154

Author(s):

Akihiko Takahashi ◽

Soichiro Takahashi

Keyword(s):

Fuzzy Logic ◽

Dynamic Environment ◽

Fuzzy Logic System ◽

Financial Investment ◽

Interval Type ◽

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Identification of continuous stirred tank reactor based on PCA-interval type-2 fuzzy logic system method

Procedia Computer Science ◽

10.1016/j.procs.2021.02.053 ◽

2021 ◽

Vol 183 ◽

pp. 230-236

Author(s):

Zhengmei Zhao ◽

Jun Li

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic System ◽

Stirred Tank ◽

Continuous Stirred Tank Reactor ◽

Tank Reactor ◽

System Method ◽

Continuous Stirred Tank ◽

Interval Type ◽

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Diagnosing of Risk State in Subsystems of CNC Turning Center using Interval Type-2 Fuzzy Logic System with Semi Elliptic Membership Functions

International Journal of Fuzzy Systems ◽

10.1007/s40815-021-01172-0 ◽

2021 ◽

Author(s):

K. B. Badri Narayanan ◽

M. Sreekumar

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic System ◽

Membership Functions ◽

Cnc Turning ◽

Turning Center ◽

Interval Type ◽

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Detection and classification of multiple power signal patterns with Volterra series and interval type-2 fuzzy logic system

Protection and Control of Modern Power Systems ◽

10.1186/s41601-017-0039-z ◽

2017 ◽

Vol 2 (1) ◽

Author(s):

Rahul ◽

Rajiv Kapoor ◽

M. M. Tripathi

Keyword(s):

Fuzzy Logic ◽

Volterra Series ◽

Fuzzy Logic System ◽

Multiple Power ◽

Interval Type ◽

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Interval type-2 fuzzy logic system for the double tank water level control system

2017 9th International Conference on Modelling, Identification and Control (ICMIC) ◽

10.1109/icmic.2017.8321608 ◽

2017 ◽

Author(s):

Wen Zhang ◽

Ruisheng Sun

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Water Level ◽

Fuzzy Logic System ◽

Level Control ◽

Level Control System ◽

Interval Type ◽

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Fault Detection Method based on Auto-associative Kernel Regression and Interval Type-2 Fuzzy Logic System for Multivariate Process

2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) ◽

10.1109/fuzz45933.2021.9494486 ◽

2021 ◽

Author(s):

Seunghwan Jung ◽

Minseok Kim ◽

Joungguen Kim ◽

Sungshin Kim

Keyword(s):

Fuzzy Logic ◽

Fault Detection ◽

Detection Method ◽

Kernel Regression ◽

Fuzzy Logic System ◽

Multivariate Process ◽

Interval Type ◽

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Interval type-2 fuzzy model based indirect adaptive tracking control design for nonlinear systems with dead-zones

International Conference on Fuzzy Systems ◽

10.1109/fuzzy.2010.5584112 ◽

2010 ◽

Author(s):

Ho-Sheng Chen ◽

Wen-Shyong Yu

Keyword(s):

Nonlinear Systems ◽

Tracking Control ◽

Fuzzy Model ◽

Control Design ◽

Adaptive Tracking Control ◽

Adaptive Tracking ◽

Model Based ◽

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