Evolutionary algorithm-based parameter identification for nonlinear dynamical systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The inverse problem of parameter estimation for Duffing oscillator, a chaotic dynamical system well known in engineering is solved using quantum-inspired evolutionary algorithm, differential evolution and genetic algorithms. The paper focuses on such combination of parameters that produce periodic responses instead of purely chaotic responses. The feature set used is a set of displacement values of the first five Poincaré points, after ignoring transient effects. All approaches correctly identify the target set of parameters as producing the given response; however, depending on the fitness landscape some parameters are more difficult to identify than others especially when using the canonical genetic algorithm. This paper is also the first to investigate the quantum-inspired evolutionary algorithm for such parameter identification problems.

Original languageEnglish (US)
Title of host publication2011 IEEE Congress of Evolutionary Computation, CEC 2011
Pages1-5
Number of pages5
DOIs
StatePublished - 2011
Event2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA, United States
Duration: Jun 5 2011Jun 8 2011

Other

Other2011 IEEE Congress of Evolutionary Computation, CEC 2011
CountryUnited States
CityNew Orleans, LA
Period6/5/116/8/11

Fingerprint

Nonlinear dynamical systems
Nonlinear Dynamical Systems
Parameter Identification
Evolutionary algorithms
Evolutionary Algorithms
Identification (control systems)
Genetic algorithms
Inverse problems
Genetic Algorithm
Parameter estimation
Chaotic Dynamical Systems
Dynamical systems
Duffing Oscillator
Fitness Landscape
Differential Evolution Algorithm
Identification Problem
Parameter Estimation
Inverse Problem
Engineering
Target

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

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title = "Evolutionary algorithm-based parameter identification for nonlinear dynamical systems",
abstract = "The inverse problem of parameter estimation for Duffing oscillator, a chaotic dynamical system well known in engineering is solved using quantum-inspired evolutionary algorithm, differential evolution and genetic algorithms. The paper focuses on such combination of parameters that produce periodic responses instead of purely chaotic responses. The feature set used is a set of displacement values of the first five Poincar{\'e} points, after ignoring transient effects. All approaches correctly identify the target set of parameters as producing the given response; however, depending on the fitness landscape some parameters are more difficult to identify than others especially when using the canonical genetic algorithm. This paper is also the first to investigate the quantum-inspired evolutionary algorithm for such parameter identification problems.",
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Banerjee, A & Abu-Mahfouz, I 2011, Evolutionary algorithm-based parameter identification for nonlinear dynamical systems. in 2011 IEEE Congress of Evolutionary Computation, CEC 2011., 5949590, pp. 1-5, 2011 IEEE Congress of Evolutionary Computation, CEC 2011, New Orleans, LA, United States, 6/5/11. https://doi.org/10.1109/CEC.2011.5949590

Evolutionary algorithm-based parameter identification for nonlinear dynamical systems. / Banerjee, Amit; Abu-Mahfouz, Issam.

2011 IEEE Congress of Evolutionary Computation, CEC 2011. 2011. p. 1-5 5949590.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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