Laser welding of thin sheets has widespread application in various fields such as battery manufacturing, automobiles, aviation, electronics circuits and medical sciences. Hence, it is very essential to develop a predictive model using artificial intelligence order achieve high-quality weldments an economical manner. In the present study, two advanced techniques, namely adaptive neuro-fuzzy infe...

this paper presents fuzzy and conventional performance of model reference adaptive control(mrac) to control a dc drive. the aims of this work are achieving better match of motor speed with reference speed, decrease of noises under load changes and disturbances, and increase of system stability. the operation of nonadaptive control and the model reference of fuzzy and conventional adaptive contr...

The paper deals with the problems of robust fault detection using soft computing techniques, in particular neural networks (Group Method of Data Handling, GMDH), multi-layer perceptron), and neuro-fuzzy networks (Takagi-Sugeno model). The model based approach to Fault Detection and Isolation (FDI) is considered. The main objective is to show how to employ the bounded-error approach to determine...

The growth in the demand of electrical energy is leading to load on the Power system which increases the occurrence of frequent oscillations in the system. The reason for the oscillations is due to the lack of damping torque which is required to dominate the disturbances of Power system. By using FACT devices, such as Unified Power Flow Controller (UPFC) can control power flow, reduce sub-synch...

Solubility of carbon dioxide in poly(vinyl acetate) (PVAc), poly(2,6-dimethyl-1,4-phenylene ether) (PPO), polypropylene (PP), and high-density polyethylene (HDPE), poly(butylene succinate) (PBS), poly(butylene succinate-co-adipate) (PBSA) and polystyrene (PS) are modeled by adaptive neuro-fuzzy inference system (ANFIS) in wide range of pressure and temperature. The results obtained in this work...

An adaptive neuro-fuzzy inference systems (ANFIS) model was used for predicting regional average wind speed and power values in the Central Anatolian region of Turkey. In model development, longitude, latitude and altitude of wind stations and wind speed measurement height were taken as input variables, while wind speed and power values were taken as output variables for 4 different surface rou...

Accurate load forecasting helps stabilize the system by triggering the appropriate actions if needed such as planning for emergency dispatch and load switching for short-term solution and building or upgrading facilities for long-term solution. The Short Term Load Forecasting (STLF) provides information for utilities’ system planners so that they can come up with a short-term solution to protec...

This chapter presents the modeling and simulation of an adaptive neuro-fuzzy inference strategy (ANFIS) to control one of the most important parameters of the induction machine, viz., speed. IM’s are non-linear machines having a complex and time-varying dynamics. Some of the states are inaccessible during the operational stages and also many of the states are not available for measurements; hen...

The summer season of 2003 in Continental Portugal was by far the worst in what respects both to the number of forest fires and the amount of burnt area. In the present work, burnt area monitoring was performed using NOAA/AVHRR imagery by means of a neuro-fuzzy (ANFIS) algorithm that was applied on an operational basis to the surface of the country. Validation of obtained results was performed b...

Gas turbines are currently a popular power generation technology in countries with access to natural gas resources. However they are very complex systems the operation of which at peak performance is challenging. This paper proposes the use of a hybrid approach based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the control of the speed and the exhaust temperature of a gas turbine. Th...