In this paper, an adaptive neuro fuzzy interference (ANFIS) based hybrid field oriented speed controlling of an induction motor is proposed. The proposed hybrid field oriented speed controller results attractive performance of induction motor with the potential features of both Artificial Neural network (ANN) and Fuzzy Logic Controller (FLC). In this topology the Artificial Neural Network (ANN)...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...

Abstract Electroencephagram (EEG) is the recording of electrical activity of the brain. Though it is intended to record cerebral signals,it also records the signals that are not of cerebral origin called artifacts. Artifact removal from EEG signals is essential for better diagnosis. This paper proposes a hybrid learning algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for elimin...

introduction: evaporation and evapotranspiration are two major components of hydrological cycle which are very important for agricultural studies as well as water resources management. so far, various methods have been addressed for the estimation of daily reference crop evapotranspiration (et0). among them, fao penman-montieth 56 (pmf-56) (allen et al., 1998) is widely used as a standard metho...

The application of neuro-fuzzy inference system to predict the compressive strengths of concrete is presented in this study. To investigate the influence of various parameters which affect the compressive strength, 2000 data samples were used for the analysis. Adaptive neuro-fuzzy inference system (ANFIS) was introduced for training and testing the data obtained from technical literatures. To r...

This paper concentrated on the design and analysis of Neuro-Fuzzy controller based Adaptive Neuro-Fuzzy inference system (ANFIS) architecture for Load frequency control of interconnected areas, to regulate the frequency deviation and power deviations. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead ...

The paper presents a methodology for developing adaptive speed controllers in a permanent-magnet brushless DC (BLDC) motor drive system. A proportional-integral controller is employed in order to obtain the controller parameters at each selected load. The resulting data from PI controller are used to train adaptive neuro-fuzzy inference systems (ANFIS) that could deduce the controller parameter...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track rotational speed of a reference engine and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the system is developed and simulation results are presented. It is shown that the ANFIS controller is suitable for control systems with large time d...

Predicting water quality is the key factor in the water quality management of reservoirs. Since a large number of factors affect the water quality, traditional data processing methods are no longer good enough for solving the problem. The dissolved oxygen (DO) level is a measure of the health of the aquatic system and its prediction is very important. DO dynamics are highly nonlinear and artifi...

weather process prediction is the tool for managers to planning the future political for maximum operation. the aim of this research is relation investigation of large scale synoptically patterns with seasonal rainfall of khorasan province. in this research, we have analyzed 37 years of rainfall data in khorasan province that is located the northeastern part of iran .we attempted to train adapt...