TY - GEN
T1 - Comparative study of evolutionary algorithms for parameter identification of an impact oscillator
AU - Banerjee, Amit
AU - Abu-Mahfouz, Issam
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The use of non-classical evolutionary optimization techniques such as genetic algorithms, differential evolution, swarm optimization and genetic programming to solve the inverse problem of parameter identification of dynamical systems leading to chaotic states has been gaining popularity in recent years. In this paper, three popular evolutionary algorithms-differential evolution, particle swarm optimization and the firefly algorithm are used for parameter identification of a clearance-coupled-impact oscillator system. The behavior of impacting systems is highly nonlinear exhibiting a myriad of harmonic, low order and high order sub-harmonic resonances, as well as chaotic vibrations. The time-history simulations of the single-degree-of-freedom impact oscillator were obtained by the Neumark-b numerical integration algorithm. The results are illustrated by bifurcation graphs, state space portraits and Poincare' maps which gives valuable insights on the dynamics of the impact system. The parameter identification problem relates to finding one set of system parameters given a chaotic or periodic system response as a set of Poincaré points and a different but known set of system parameters. The three evolutionary algorithms are compared over a set of parameter identification problems. The algorithms are compared based on solution quality to evaluate the efficacy of using one algorithm over another.
AB - The use of non-classical evolutionary optimization techniques such as genetic algorithms, differential evolution, swarm optimization and genetic programming to solve the inverse problem of parameter identification of dynamical systems leading to chaotic states has been gaining popularity in recent years. In this paper, three popular evolutionary algorithms-differential evolution, particle swarm optimization and the firefly algorithm are used for parameter identification of a clearance-coupled-impact oscillator system. The behavior of impacting systems is highly nonlinear exhibiting a myriad of harmonic, low order and high order sub-harmonic resonances, as well as chaotic vibrations. The time-history simulations of the single-degree-of-freedom impact oscillator were obtained by the Neumark-b numerical integration algorithm. The results are illustrated by bifurcation graphs, state space portraits and Poincare' maps which gives valuable insights on the dynamics of the impact system. The parameter identification problem relates to finding one set of system parameters given a chaotic or periodic system response as a set of Poincaré points and a different but known set of system parameters. The three evolutionary algorithms are compared over a set of parameter identification problems. The algorithms are compared based on solution quality to evaluate the efficacy of using one algorithm over another.
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U2 - 10.1115/IMECE2014-38855
DO - 10.1115/IMECE2014-38855
M3 - Conference contribution
AN - SCOPUS:84926373930
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Dynamics, Vibration, and Control
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014
Y2 - 14 November 2014 through 20 November 2014
ER -