Multi-parameter identification from scalar time series generated by a Malkus-Lorenz water wheel

DOI10.1063/1.3689441zbMath1331.37119OpenAlexW1991810030WikidataQ51391809 ScholiaQ51391809MaRDI QIDQ2787727

Daniel W. Hahs, Alison M. Saunders, Lucas Illing

Publication date: 4 March 2016

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/c0696cffce3917e429aab86b78f1797ee15e54b9

Mathematics Subject Classification ID

Transition to stochasticity (chaotic behavior) for nonlinear problems in mechanics (70K55) Time series analysis of dynamical systems (37M10) Dynamical systems in classical and celestial mechanics (37N05)

Related Items (2)

Chaos control and solutions of fractional-order Malkus waterwheel model ⋮ Adaptive synchronization design for uncertain chaotic systems in the presence of unknown system parameters: a revisit

Cites Work

• Unnamed Item
• Adaptive observer-based synchronization of the nonlinear nonpassifiable systems
• A study of the asymmetric Malkus waterwheel: The biased Lorenz equations
• Parameter identification and projective synchronization between different chaotic systems
• Identifiability and observability analysis for experimental design in nonlinear dynamical models
• Using synchronization of chaos to identify the dynamics of unknown systems
• Adaptive observer for multiple-input-multiple-output (MIMO) linear time-varying systems
• Power spectra for deterministic chaotic dynamical systems

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