Applications of neuro fuzzy systems: A brief review and future outline
This paper surveys neuro fuzzy systems (NFS) development using classification and
literature review of articles for the last decade (2002–2012) to explore how various NFS …
literature review of articles for the last decade (2002–2012) to explore how various NFS …
[HTML][HTML] A survey on advancement of hybrid type 2 fuzzy sliding mode control
Numerous types of hybridizations between type 2 fuzzy logic system (T2FLS) and sliding
mode control (SMC) have been proposed to construct an intelligent and robust controller …
mode control (SMC) have been proposed to construct an intelligent and robust controller …
Adaptive neuro-fuzzy control of a spherical rolling robot using sliding-mode-control-theory-based online learning algorithm
As a model is only an abstraction of the real system, unmodeled dynamics, parameter
variations, and disturbances can result in poor performance of a conventional controller …
variations, and disturbances can result in poor performance of a conventional controller …
Overview of type-2 fuzzy logic systems
AT Azar - International Journal of Fuzzy System Applications …, 2012 - igi-global.com
Fuzzy set theory has been proposed as a means for modeling the vagueness in complex
systems. Fuzzy systems usually employ type-1 fuzzy sets, representing uncertainty by …
systems. Fuzzy systems usually employ type-1 fuzzy sets, representing uncertainty by …
Control of omnidirectional robot using z-number-based fuzzy system
The control of mobile robots in an uncertain environment that is densely cluttered with
dynamic obstacles is an important problem in robotics. A fuzzy set theory is one of the …
dynamic obstacles is an important problem in robotics. A fuzzy set theory is one of the …
A meta-cognitive sequential learning algorithm for neuro-fuzzy inference system
K Subramanian, S Suresh - Applied soft computing, 2012 - Elsevier
In this paper, we present a meta-cognitive sequential learning algorithm for a neuro-fuzzy
inference system, referred to as,'Meta-Cognitive Neuro-Fuzzy Inference System'(McFIS) …
inference system, referred to as,'Meta-Cognitive Neuro-Fuzzy Inference System'(McFIS) …
Type-2 fuzzy tool condition monitoring system based on acoustic emission in micromilling
In this paper, a micromilling type-2 fuzzy tool condition monitoring system based on multiple
AE acoustic emission signal features is proposed. The type-2 fuzzy logic system is used as …
AE acoustic emission signal features is proposed. The type-2 fuzzy logic system is used as …
A survey-based type-2 fuzzy logic system for energy management in hybrid electrical vehicles
Hybrid electrical vehicles combine two or more energy sources (at least one electrical) to
benefit from their different characteristics regarding autonomy, reversibility and dynamic …
benefit from their different characteristics regarding autonomy, reversibility and dynamic …
Online identification of evolving Takagi–Sugeno–Kang fuzzy models for crane systems
This paper suggests new evolving Takagi–Sugeno–Kang (TSK) fuzzy models dedicated to
crane systems. A set of evolving TSK fuzzy models with different numbers of inputs are …
crane systems. A set of evolving TSK fuzzy models with different numbers of inputs are …
A context layered locally recurrent neural network for dynamic system identification
R Coban - Engineering Applications of Artificial Intelligence, 2013 - Elsevier
This paper puts forward a novel recurrent neural network (RNN), referred to as the context
layered locally recurrent neural network (CLLRNN) for dynamic system identification. The …
layered locally recurrent neural network (CLLRNN) for dynamic system identification. The …