ADAPTIVE NEURO-FUZZY KOHONEN’S NETWORK

Neuro-fuzzy Network Based Adaptive Integrating Cotnrol

A self-tuning neurofuzzy integrating controller is derived in this paper for offset eliminating purpose. CARIMA plant model is used and the control law produces integral control terms in a natural way. Neurofuzzy networks are chosen to implement the direct self-tuning nonlinear integrating controller. The performance of the self-tuning integrating neurofuzzy controller is illustrated by example...

Adaptive Neuro-Fuzzy Systems

One benefit of fuzzy systems (Zadeh, 1965; Ruspini et al., 1998; Cox, 1994) is that the rule base can be created from expert knowledge, used to specify fuzzy sets to partition all variables and a sufficient number of fuzzy rules to describe the input/output relation of the problem at hand. However, a fuzzy system that is constructed by expert knowledge alone will usually not perform as required...

Adaptive Neuro-Fuzzy Systems

Prediction of Thermal performance nanofluid Al2O3 by Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systemt

In recent years, the use of modeling methods that directly utilize empirical data is increasing due to the high accuracy in predicting the results of the process, rather than statistical methods. In this paper, the ability of Artificial Neural Network (ANN) and Adaptive Fuzzy-Neural Inference System (ANFIS) models in the prediction of the thermal performance of Al2O3 nanofluid that is measured ...

A Learning Algorithm for Forecasting Adaptive Wavelet-neuro- Fuzzy Network

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...