Results 11 to 20 of about 31,148 (230)
ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers [PDF]
In this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS.
César Manuel Braz, Barros Rui Carneiro
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Prediction in Photovoltaic Power by Neural Networks [PDF]
The ability to forecast the power produced by renewable energy plants in the short and middle term is a key issue to allow a high-level penetration of the distributed generation into the grid infrastructure. Forecasting energy production is mandatory for
Antonello Rosato +3 more
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Wind energy has been developed and is widely used as a clean and renewable form of energy. Among the existing variety of wind turbines, variable-speed variable-pitch wind turbines have become popular owing to their variable output power capability.
Ya-Jun Fan, Hai-tong Xu, Zhao-Yu He
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This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-
Abdessamad Intidam +6 more
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In complex industrial processes (CIPs), due to technical and economic limitations, key performance indicators (KPIs), especially the chemical content-related KPIs, are often difficult to measure in real time, which hinders the propagation of advanced ...
Jinping Liu +5 more
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Neuro-fuzzy control of sit-to-stand motion using head position tracking
Based on the clinical evidence that head position measured by the multisensory system contributes to motion control, this study suggests a biomechanical human-central nervous system modeling and control framework for sit-to-stand motion synthesis ...
Samina Rafique +3 more
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Controlling an uncertain mechatronic system is challenging and crucial for its automation. In this regard, several control-strategies are developed to handle such systems.
Muhammad Khurram Saleem +4 more
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Artificial intelligence-based approaches for multi-station modelling of dissolve oxygen in river [PDF]
: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve ...
G. Elkiran +3 more
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Purpose: Neuro-fuzzy systems aim to combine the benefits of artificial neural networks and fuzzy inference systems: a neural network can learn patterns from data and achieves high performance, whereas a fuzzy system matches inputs and outputs using ...
Hafsaa Ouifak, Ali Idri
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Using an adaptive fuzzy-logic system to optimize the performances and the reduction of chattering phenomenon in the control of induction motor [PDF]
Neural networks and fuzzy inference systems are becoming well recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance.
Barazane Linda +3 more
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