Intelligent multivariable air-quality forecasting system based on feature selection and modified evolving interval type-2 quantum fuzzy neural network
J Wang, H Li, H Yang, Y Wang - Environmental Pollution, 2021 - Elsevier
Owing to the high nonlinearity and noise in the air quality index (AQI), tackling the
uncertainties and fuzziness in the forecasting process is still a prevalent problem. Therefore …
uncertainties and fuzziness in the forecasting process is still a prevalent problem. Therefore …
Adaptive composite dynamic surface neural control for nonlinear fractional-order systems subject to delayed input
In the article, the adaptive composite dynamic surface neural controller design problem for
nonlinear fractional-order systems (NFOSs) subject to delayed input is discussed. A …
nonlinear fractional-order systems (NFOSs) subject to delayed input is discussed. A …
NeuroQuMan: Quantum neural network-based consumer reaction time demand response predictive management
A Safari, MA Badamchizadeh - Neural Computing and Applications, 2024 - Springer
Demand response, and artificial intelligence integration with it, have a considerable effect in
optimizing energy consumption, grid stability, and promoting sustainable energy practices …
optimizing energy consumption, grid stability, and promoting sustainable energy practices …
Intelligent fractional-order backstepping control for an ironless linear synchronous motor with uncertain nonlinear dynamics
SY Chen, TH Li, CH Chang - ISA transactions, 2019 - Elsevier
This study aims to develop an intelligent fractional-order backstepping controller to control
the mover position of an ironless permanent magnet linear synchronous motor. First, we …
the mover position of an ironless permanent magnet linear synchronous motor. First, we …
Adaptive type-2 fuzzy PID controller for LFC in AC microgrid
An AC microgrid (MG) system links the distributed generation (DG) based on renewable
energy resources and local electrical loads in modern power systems. Intermittent …
energy resources and local electrical loads in modern power systems. Intermittent …
MTN output feedback tracking control for MIMO discrete-time uncertain nonlinear systems
HS Yan, QM Sun - ISA transactions, 2021 - Elsevier
An adaptive controller is developed that is based on the multidimensional Taylor network
(MTN). This controller is used for multi-input and multi-output (MIMO) uncertain discrete-time …
(MTN). This controller is used for multi-input and multi-output (MIMO) uncertain discrete-time …
A novel robust adaptive control using RFWNNs and backstepping for industrial robot manipulators with dead-zone
This paper proposes a novel robust adaptive-backstepping-recurrent-fuzzy-wavelet-neural-
networks controller (ABRFWNNs) based on dead zone compensator for Industrial Robot …
networks controller (ABRFWNNs) based on dead zone compensator for Industrial Robot …
Decentralized adaptive neural prescribed performance control for high-order stochastic switched nonlinear interconnected systems with unknown system dynamics
W Si, X Dong, F Yang - ISA transactions, 2019 - Elsevier
In this paper, the problem of decentralized adaptive neural backstepping control is
investigated for high-order stochastic nonlinear systems with unknown interconnected …
investigated for high-order stochastic nonlinear systems with unknown interconnected …
Development of the intelligent oil field with management and control using iiot (industrial internet of things)
AS Allahloh, S Mohammad - 2018 2nd IEEE International …, 2018 - ieeexplore.ieee.org
In the past decade there is a huge development in artificial intelligence technologies for
various applications. Credit goes to recent researches which have increased the computing …
various applications. Credit goes to recent researches which have increased the computing …
Feedback error learning-based type-2 fuzzy neural network predictive controller for a class of nonlinear input delay systems
In this paper, a type-2 fuzzy neural network predictive (T2FNNP) controller has been
designed in the feedback error learning (FEL) framework for a class of input delay nonlinear …
designed in the feedback error learning (FEL) framework for a class of input delay nonlinear …