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
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