This paper presents an investigation into the comparative performance of intelligent system identification and control algorithms within the framework of an active vibration control (AVC) system. Evolutionary Genetic algorithms (GAs) and Adaptive Neuro-Fuzzy Inference system (ANFIS) algorithms are used to develop mechanisms of an AVC system, where the controller is designed on the basis of opti...

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function ...

Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flo...

The Adaptive Neuro-Fuzzy Inference System (ANFIS) combines the strengths of both Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) into a single framework. By doing so, it allows for quicker learning adaptable interpretation capabilities, which are useful modeling complex patterns identifying nonlinear relationships. One significant challenge in assessing water quality is difficulty time-c...

This paper deals with static hysteresis modeling for the PAM-based (pneumatic artificial muscles) position servosystem by means of an adaptive neuro-fuzzy inference system. The hysteretic behavior is expressed in arm position-pressure difference dependence where the output variable (arm position) depends on the history of input variable (pressure difference). In this way, a first order (until i...

The application of the neuro-fuzzy inference system to predict the compressive strength of concrete is presented in this study. The adaptive neuro-fuzzy inference system (ANFIS) is introduced for training and testing the data sets consisting of various parameters. To investigate the influence of various parameters which affect the compressive strength, 1551 data pairs are collected from the tec...

This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consist...

The utilization of a microgrid with photovoltaic (PV) and wind generation system presents challenge due to their voltage power output variations. This problem is majorly addressed within the converter section using maximum point tracking (MPPT) algorithms regulation strategies. paper an interleaved boost (IBC) modeling control hybrid adaptive neuro-fuzzy inference system-proportional plus integ...

Abstract Indonesia is one of the most important centers for biodiversity in world with highest level endemism. Meanwhile, tourism and strategic economic sectors future. It hoped that development industry will also be able to support efforts conserve nature, biological wealth, national cultural wealth. The identification planning needs done more detail carefully. In this article, prediction mode...