Title :
Identification and Prediction of Nonlinear Dynamical Plants Using TSK and Wavelet Neuro-Fuzzy Models
Author :
Banakar, Ahmad ; Azeem, Mohammad Fazle
Author_Institution :
Dept. of Electr. Eng., Aligarh Muslim Univ.
Abstract :
The problem of identification consists of setting up a suitably parameterized identification model and adjusting the parameters of the model by optimizing a performance index. Parallel and parallel-series identification methods are used to adjust an unknown model´s parameters. In this paper a combined parallel/series-parallel identification model, based on TSK fuzzy model and wavelet neuro-fuzzy model, is proposed
Keywords :
fuzzy neural nets; identification; nonlinear dynamical systems; performance index; wavelet transforms; TSK fuzzy model; nonlinear dynamical plant identification; nonlinear dynamical plant prediction; parallel-series identification; parameterized identification model; performance index optimization; unknown model parameter; wavelet neurofuzzy model; Feedforward neural networks; Fuzzy systems; Heuristic algorithms; Intelligent systems; Mathematical model; Neural networks; Power system modeling; Predictive models; Time frequency analysis; Uncertainty; Parallel and Series-Parallel identification model; TSK fuzzy model; Wavelet Neuro-Fuzzy model;
Conference_Titel :
Intelligent Systems, 2006 3rd International IEEE Conference on
Conference_Location :
London
Print_ISBN :
1-4244-01996-8
Electronic_ISBN :
1-4244-01996-8
DOI :
10.1109/IS.2006.348490
