Abstrakt

Rule Weight Base Behavioural Modeling of Steam Turbine Using Genetically Tuned Adaptive Network Based Fuzzy Inference System

D. N. Dewangan, Dr. Y. P. Banjare, Dr. Manoj Kumar Jha

In view nonlinearities, steam turbine complex structure of dynamic modelling, selection of suitable configuration of adaptive network based fuzzy inference system (ANFIS) and minimizing the modelling error, a rule weight base behavioural system modelling of steam turbine (genetically tuned ANFIS) model has proposed to solve the problem through the assessment of enthalpy and power output of the system. The accuracy and performance of enthalpy estimation over wide range of operation data has estimated with reference to integral square error (ISE) criterion. This technique is useful in order to adjust model parameters over full range of input output operational data. From this work, it is clearly evident that the error obtained from conventional ANFIS structure is much higher than that of obtained from ANFIS structure after genetically tuning.