This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is classical proportional integral (PI) controller. In contrast, second one based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive system (PI-ANFIS) and particle swarm optimization-proportional (PSO-PI-ANFIS)). objective regul...

The oxidative coupling of methane (OCM) performance over Na-W-Mn/SiO2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (ANFIS) using reaction data gathered in an isothermal fixed bed microreactor. In the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (GHSV), and reaction temperature were conside...

In recent years, soft computing and artificial intelligence techniques such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been effectively used in various civil engineering applications. This study aims to examine the potential of ANN and ANFIS for modeling the compressive strength of concrete containing expanded perlite powder (EPP). For doing this, ...

This paper presents the design and analysis of Neuro-Fuzzy controller based on 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 to s...

A new impulsive noise (IN) elimination filter, entitled adaptive neuro-fuzzy inference system-based IN removal filter (Anfis-F), which shows high performance at the restoration of images distorted by IN, is proposed in this paper. The Anfis-F comprises three main steps: finding the pixels that are suspected to be corrupted, the Delaunay triangulation, and finally, making estimation for intensit...

This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy controller shows better results in comparison to triangular fuzzy controller. Secondly, ...

In this paper, an Adaptive Neuro Fuzzy Interference System (ANFIS) is proposed for eliminating voltage harmonics present in the multilevel inverter. It is achieved by reducing the THD present in the multilevel inverter output voltage. Here, the voltage variation of the multilevel inverter is determined from the actual load voltage and the reference voltage. The voltage variation at different ti...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System (ANFIS). We examine the period 1950-2009, where we take as the in-sample or training period 1950-2005, ...

A new hybrid filtering technique is proposed to improving denoising process on digital images. This technique is performed in two steps. In the first step, gaussian noise and impulse noise is eliminated using decision based algorithm (DBA). Image denoising process is further improved by an appropriately combining DBA with Adaptive Neuro Fuzzy Inference System (ANFIS) at the removal of gaussian ...