### 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 language | English (US) |
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Title of host publication | 2011 IEEE Congress of Evolutionary Computation, CEC 2011 |

Pages | 1-5 |

Number of pages | 5 |

DOIs | |

State | Published - 2011 |

Event | 2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA, United States Duration: Jun 5 2011 → Jun 8 2011 |

### Other

Other | 2011 IEEE Congress of Evolutionary Computation, CEC 2011 |
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Country | United States |

City | New Orleans, LA |

Period | 6/5/11 → 6/8/11 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computational Theory and Mathematics
- Theoretical Computer Science

### Cite this

*2011 IEEE Congress of Evolutionary Computation, CEC 2011*(pp. 1-5). [5949590] https://doi.org/10.1109/CEC.2011.5949590

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*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.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Evolutionary algorithm-based parameter identification for nonlinear dynamical systems

AU - Banerjee, Amit

AU - Abu-Mahfouz, Issam

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=80051993440&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80051993440&partnerID=8YFLogxK

U2 - 10.1109/CEC.2011.5949590

DO - 10.1109/CEC.2011.5949590

M3 - Conference contribution

SN - 9781424478347

SP - 1

EP - 5

BT - 2011 IEEE Congress of Evolutionary Computation, CEC 2011

ER -