This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

Intelligent energy management has become one of the major research fields in electrical engineering. It constitutes an important tool for efficient planning and operation of power systems and its significance has been intensifying particularly, because of the recent movement towards open energy markets and the need to assure high standards on reliability. Hybrid neuro-fuzzy paradigms have recen...

In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating p...

Performance of a fuzzy system identifier is investigated against a fossil fuel boiler data. A multi-layer neuro-ftrzzy system presents identification of a drum type boiler. This identification techruque provides a rule-based approach to express the boiler dynamics in fuzzy rules that are generated from the experimental boiler data. The interconnections of neuro-fuzzy layers furnish these fuzzy ...

In this study the Dissolved Air Flotation (DAF) system in oil refinery was investigated for the treatment of refinery wastewater. In order to investigate sytem a labratory scale rig was built. The aim is to remove some of the wastewater pollutant materials and data modeling of COD test.The effect of several parameters on flotation efficiency namely, saturator pressure, and coagulant dose, on CO...

In this paper, we present a comparative study on applications of Neuro Fuzzy and Support Vector Machines (SVMs) for pattern recognition. Since SVMs show good generalization performance on many real-life data and the approach is properly motivated theoretically, it has been applied to wide range of applications. This paper describes a brief introduction of SVMs and summarizes its numerous applic...

The architecture of forecasting adaptive wavelet-neuro-fuzzy-network and its learning algorithm for the solving of nonstationary processes forecasting tasks are proposed. The learning algorithm is optimal on rate of convergence and allows to tune both the synaptic weights and dilations and translations parameters of wavelet activation functions. The simulation of developed wavelet-neuro-fuzzy n...

The architecture of adaptive wavelet-neuro-fuzzy-network and its learning algorithm for the solving of nonstationary processes forecasting and emulation tasks are proposed. The learning algorithm is optimal on rate of convergence and allows tuning both the synaptic weights and dilations and translations parameters of wavelet activation functions. The simulation of developed wavelet-neuro-fuzzy ...

In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...