A Proportional-Integral (PI) controller and a non-linear Fuzzy and Neuro controller is designed and its application to the regulation of 54V, 2.916kW Quasi-Resonant Buck Converter is comparatively investigated. PI controller involves Proportional gain (Kp) and Integral time (Ki) parameters whose manual tuning provides an appropriate action. Fuzzy logic is on the notion of graded membership and ...

This paper presents an adaptive neuro-fuzzy controller ANFIS (Adaptive Neuro-Fuzzy Inference System) for a bilateral teleoperation system based on FPGA (Field Programmable Gate Array). The proposed controller combines the learning capabilities of neural networks with the inference capabilities of fuzzy logic, to adapt with dynamic variations in master and slave robots and to guarantee good prac...

This paper deals with the Artificial Intelligent control of Doubly-Fed Induction Generator using Adaptive Neuro-Fuzzy Inference System in order to generate maximum power at variable wind speed. The rotor control is achieved here using the combined features of neural network and fuzzy logic controller.

The main objective of this paper is to study how can we sense the position of a brushless D.C Motor using artificial neural network/ fuzzy logic/neuro-fuzzy combination?The simulation will be MATLAB/SIMULINK based. We are change the mode of sensing from hall sensors to other form.

-In the present world the security vulnerabilities are highly challenging in MANET. To get the maximum security and minimum threat there is lots of work going on. To effectively isolate the malicious node this paper proposes a Neuro fuzzy algorithm. By using fuzzy logic we can further improve the security level by identifying the malicious node more accurately. The concept behind the paper is a...

In this study, we explored hybrid fuzzy logic modelling techniques to predict the burned area of forest fires. Fast detection is crucial for successful firefighting, and a model with an accurate prediction ability extremely useful optimizing fire management. Fuzzy Inductive Reasoning (FIR) Adaptive Neuro-Fuzzy Inference System (ANFIS) are two powerful areas forests in Portugal. The results obta...

this paper presents the bio-inspired neurofuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to fulfill all the preferred requirements of...

314 Abstract— Neuro-Fuzzy systems are hybrid intelligent systems which combine features of both paradigmsfuzzy logic and artificial neural networks. Adaptive Neuro Fuzzy Inference System (ANFIS) is one of such architecture which is widely used as solution for various real world problems. This paper describes development of an ANFIS model for FPGA implementation. Model can be realized with hardw...

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...

Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decisionmaking model combining fuzzy log...