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neuro-fuzzy control systems

Performance Improvement for BLDC Motor by using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

Performance Improvement for BLDC Motor by using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

... Adaptive Neuro-Fuzzy Inference Systems (ANFIS) algorithm are considered and included to replace the conventional method of Proportional Integral and ...and fuzzy logic principles, it has ...

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Radial Basis Function Neural Network Trained by Adaptive Chaotic Particle Swarm Optimization to Control Nonlinear Systems

Radial Basis Function Neural Network Trained by Adaptive Chaotic Particle Swarm Optimization to Control Nonlinear Systems

... The neuro-fuzzy controller considered in this comparative study was proposed in (Pham and Xing, ...the fuzzy inference ...Seven fuzzy sets are used for each of these input variables; as a ...

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Designs Neuro Fuzzy Models in Control Problems of a Steam Heater

Designs Neuro Fuzzy Models in Control Problems of a Steam Heater

... usable control systems is complicated by the change in the dynamic characteristics of individual elements of boiler units depending on the load and other factors, as well as the significant transport delay ...

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Cultural Steward – New Role for HR

Cultural Steward – New Role for HR

... inventory control is important thing for food ...inventory control is able to adapt to changes in the environment, maintain system performance and stability in the face of various problems in the industry, ...

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Control of PMSM using Neuro-Fuzzy Based SVPWM Technique

Control of PMSM using Neuro-Fuzzy Based SVPWM Technique

... Dr.D.Vijaya Kumar completed his graduation in Electrical and Electronics Engineering from Andhra University, Visakhapatnam in 1997 and received his M.E.in Power Systems from Andhra University, India in 2000.He ...

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Sustainable Architecture of Wind Energy Conversion System based on Neuro-Fuzzy Approach

Sustainable Architecture of Wind Energy Conversion System based on Neuro-Fuzzy Approach

... to control the ...the control in this way is quite well studied and it also implies a robust machine that needs little, or almost null, maintenance Power electronic converter facilitates electrical energy ...

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Design & Analysis of Advanced Adaptive Neuro Fuzzy Interface systems for Nonlinear Networked Control Systems

Design & Analysis of Advanced Adaptive Neuro Fuzzy Interface systems for Nonlinear Networked Control Systems

... fuzzy control for a category of single-input single-output nonlinear networked control systems with network-induced delay and data loss based on adaptive backstepping control ...

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A TSK Type Recurrent Neuro Fuzzy Systems for Fault Prognosis

A TSK Type Recurrent Neuro Fuzzy Systems for Fault Prognosis

... of systems present in the process indus- try is workshop of SCIMAT ...position control system of a nuclear power plant ...agnosis systems for industrial process often requires a simulation model ...

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Power Factor Correction of Three Phase Diode Rectifier at Input Stage Using Artificial Intelligent Techniques for DC Drive Applications

Power Factor Correction of Three Phase Diode Rectifier at Input Stage Using Artificial Intelligent Techniques for DC Drive Applications

... controller, Fuzzy Logic Controller (FLC) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and the results are compared for the power factor ...of Fuzzy controller and Adaptive ...

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Neuro-Fuzzy systems for Automatic Temperature Drying Aggregate

Neuro-Fuzzy systems for Automatic Temperature Drying Aggregate

... the control system to an unstable ...automatic control systems with fixed values of the quality control parameters of the transition process varies depending on the disturbance and ...

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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models

The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models

... the fuzzy logic and neural networks make them ideal solution in individual use for some kinds of artificial intelligent but not ...intelligent control but less satisfy for decisions making. Apart of that, ...

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MAXIMUM POWER POINT TRACKING CONTROL FOR PHOTOVOLTAIC SYSTEMS: NEURO-FUZZY APPROACH

MAXIMUM POWER POINT TRACKING CONTROL FOR PHOTOVOLTAIC SYSTEMS: NEURO-FUZZY APPROACH

... of control actions for a given fuzzy inputs ...inferred fuzzy control action into a numerical value at the output by forming the “union” of the outputs resulting from each ...output ...

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CONTROLLING PIDs USING NEURO FUZZY EXPERT SYSTEMS.

CONTROLLING PIDs USING NEURO FUZZY EXPERT SYSTEMS.

... Proportional Integral Derivative (PID) controlling mechanism is found in several applications in industries where speed of motors or induction motors is to be controlled. The PID controller is specifically useful since ...

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Efficiency of genetic algorithms in intelligent 
		hybrid control systems

Efficiency of genetic algorithms in intelligent hybrid control systems

... The paper is devoted to features of genetic algorithms application in intelligent hybrid control systems. We demonstrate a general view over the model of hybrid adaptive control system. Also we ...

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Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation

Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation

... house-building. Fuzzy logic systems, considering the city plans, the nearness to cultural, medical, training and educational buildings, the public transportations systems, the other environmental ...

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A novel optimal medium resolution remote sensing image classification using Neuro fuzzy approach

A novel optimal medium resolution remote sensing image classification using Neuro fuzzy approach

... Classification based on image segments means to classify the image objects according to class descriptions structured in a user-customized knowledge rules base. The knowledge rules base is created by the image segments’ ...

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New Approach of Stability for Time Delay Takagi Sugeno Fuzzy System Based on Fuzzy Weighting Dependent Lyapunov Functionals

New Approach of Stability for Time Delay Takagi Sugeno Fuzzy System Based on Fuzzy Weighting Dependent Lyapunov Functionals

... Takagi-Sugeno fuzzy model approach has been used to examine nonlinear systems with time-delay, and different methodologies have been proposed for ana- lysis and synthesis of this type of systems ...

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Title: An Evolving Cascade Neuro-Fuzzy System for Data Stream Fuzzy Clustering

Title: An Evolving Cascade Neuro-Fuzzy System for Data Stream Fuzzy Clustering

... An evolving cascade neuro-fuzzy system for online fuzzy clustering was proposed in this paper. Every node of each system‟s cascade solves the clustering task independently from others which makes it ...

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Evolving Intelligent Systems, eIS

Evolving Intelligent Systems, eIS

... evolving systems paradigm mimics the evolution of individuals in the Nature during their life-cycle, especially humans: learning from experience, inheritance, gradual change, knowledge generation from routine ...

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Adaptive fuzzy & Neuro Fuzzy Inference controller based MPPT for photovoltaic systems

Adaptive fuzzy & Neuro Fuzzy Inference controller based MPPT for photovoltaic systems

... adaptive neuro fuzzy inference controller is used to track the maximum power from the PV ...adaptive fuzzy logic ...adaptive neuro fuzzy to fulfill the requirement of needs of whole ...

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