DocumentCode :
562796
Title :
Artificial neural network based prediction of optimal pseudo-damping and meta-damping in oscillatory fractional order dynamical systems
Author :
Das, Saptarshi ; Pan, Indranil ; Sur, Khrist ; Das, Shantanu
Author_Institution :
Dept. of Power Eng., Jadavpur Univ., Kolkata, India
fYear :
2012
fDate :
30-31 March 2012
Firstpage :
350
Lastpage :
356
Abstract :
This paper investigates typical behaviors like damped oscillations in fractional order (FO) dynamical systems. Such response occurs due to the presence of, what is conceived as, pseudo-damping and meta-damping in some special class of FO systems. Here, approximation of such damped oscillation in FO systems with the conventional notion of integer order damping and time constant has been carried out using Genetic Algorithm (GA). Next, a multilayer feed-forward Artificial Neural Network (ANN) has been trained using the GA based results to predict the optimal pseudo and meta-damping from knowledge of the maximum order or number of terms in the FO dynamical system.
Keywords :
approximation theory; damping; genetic algorithms; multilayer perceptrons; neurocontrollers; nonlinear dynamical systems; approximation; artificial neural network based prediction; damped oscillation; genetic algorithm; integer order damping; metadamping; multilayer feedforward artificial neural network; optimal pseudodamping; oscillatory fractional order dynamical systems; time constant; Computer languages; Damping; Genetic algorithms; Artificial Neural Network (ANN); Genetic Algorithm; fractional order linear systems; meta-damping; pseudo-damping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on
Conference_Location :
Nagapattinam, Tamil Nadu
Print_ISBN :
978-1-4673-0213-5
Type :
conf
Filename :
6216029
Link To Document :
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