Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Using geometric control and chaotic synchronization to estimate an unknown model parameter.

Ubiratan S Freitas1, Elbert E N Macau, Celso Grebogi

  • 1Laboratório Associado de Computação e Matemática Aplicada, Instituto Nacional de Pesquisas Espaciais, Caixa Postal 515, 12227-010, São José dos Campos, São Paulo, Brazil. ubiratan@lac.inpe.br

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 21, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Chaotic ghosts in systems with parameter drift: Delay and control critical transitions.

Physical review. E·2026
Same author

Multiscale spatiotemporal neural network with multi-attention mechanism using brain partitioning for motor imagery recognition.

Journal of neuroscience methods·2026
Same author

Complex bifurcation structures in a Hodgkin-Huxley model of thermally sensitive neurons under periodic perturbation.

Physical review. E·2025
Same author

Adaptive Whole-Brain Dynamics Predictive Method: Relevancy to Mental Disorders.

Research (Washington, D.C.)·2025
Same author

Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition.

IEEE journal of biomedical and health informatics·2025
Same author

Transcriptomic Evidence Reveals the Dysfunctional Mechanism of Synaptic Plasticity Control in ASD.

Genes·2025
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

This study introduces a novel parameter estimation method for nonlinear systems using model synchronization. The technique ensures accurate parameter estimation by controlling the model to match the system

Area of Science:

  • Control Engineering
  • Nonlinear System Analysis
  • Parameter Estimation

Background:

  • Accurate parameter estimation is crucial for understanding and controlling nonlinear systems.
  • Existing methods may face challenges with complex nonlinear dynamics.

Purpose of the Study:

  • To present a new parameter estimation procedure for nonlinear systems.
  • To utilize model synchronization for accurate unknown parameter determination.

Main Methods:

  • Employing synchronization between a model and the target system.
  • Designing a control system using geometric nonlinear control techniques.
  • Deriving sufficient conditions for synchronization and parameter estimation.

Main Results:

Related Experiment Videos

  • Demonstrated a novel procedure for parameter estimation in nonlinear systems.
  • Successfully applied geometric nonlinear control for synchronization.
  • Established conditions for reliable parameter estimation through synchronization.

Conclusions:

  • The proposed synchronization-based method offers a robust approach to parameter estimation for nonlinear systems.
  • Geometric nonlinear control provides a powerful framework for achieving the necessary synchronization.