Article Info Abstract This paper presents a Hybrid Adaptive Neuro Fuzzy Control technique for speed control of BLDC motor drives. The proposed controller is an integration of adaptive neuro fuzzy, fuzzy PID and PD controllers. The objective is to utilize the best attribute of fuzzy PID and PD controllers, which exhibits a better response than the neuro fuzzy controllers. The error back propagat...

support vector regression (svr) is a learning method based on the support vector machine (svm) that can be used for curve fitting and function estimation. in this paper, the ability of the nu-svr to predict the catalytic activity of the fischer-tropsch (ft) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (mlp) and subtractiv...

This paper presents a hybrid neuro-fuzzy methodology to identify appropriate global logistics (GL) operational modes used for global supply chain management. The proposed methodological framework includes three main developmental phases: (1) establishment of a GL strategic hierarchy, (2) formulation of GL-mode identification rules, and (3) development of a GL-mode choice model. By integrating a...

This paper describes the fuzzy modeling of permanent magnet generator for studying its mechanical dynamic analysis. Firstly electromagnetic torque analysis of the generator is carried out using finite element based package. Then fuzzy model of the generator is developed. Performance was evaluated by comparing, integrated fuzzy model, individual fuzzy model and finite element model for the gener...

It is difficult to realize adaptive control for some complex nonlinear processes which are operated in different environments and when operation conditions are changed frequently. In this paper we propose an identifier-based adaptive control (or indirect adaptive control). The identifier uses two effective tools: multiple models and neural networks. A hysteresis switching algorithm is applied t...

in this study, detection and identification of common faults in industrial gas turbines is investigated. we propose a model-based robust fault detection(fd) method based on multiple models. for residual generation a bank of local linear neuro-fuzzy (llnf) models is used. moreover, in fault detection step, a passive approach based on adaptive threshold is employed. to achieve this purpose, the a...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

In this study, detection and identification of common faults in industrial gas turbines is investigated. We propose a model-based robust fault detection(FD) method based on multiple models. For residual generation a bank of Local Linear Neuro-Fuzzy (LLNF) models is used. Moreover, in fault detection step, a passive approach based on adaptive threshold is employed. To achieve this purpose, the a...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...