Research Output
Dynamic observers for unknown populations
  Dynamic observers are considered in the context of structured population modeling and management. Roughly, observers combine a known measured variable of some process with a model of that process to asymptotically reconstruct the unknown state variable of the model. We investigate the potential use of observers for reconstructing population distributions described by density-independent (linear) models and a class of density-dependent (nonlinear) models. In both the density-dependent and -independent cases, we show, in several ecologically reasonable circumstances, that there is a natural, optimal construction of these observers. Further, we describe the robustness these observers exhibit with respect to disturbances and uncertainty in measurement.

  • Type:

    Article

  • Date:

    31 December 2020

  • Publication Status:

    Published

  • Publisher

    Southwest Missouri State University

  • DOI:

    10.3934/dcdsb.2020232

  • ISSN:

    1531-3492

  • Funders:

    Engineering and Physical Sciences Research Council

Citation

Guiver, C., Poppelreiter, N., Rebarber, R., Tenhumberg, B., & Townley, S. (2021). Dynamic observers for unknown populations. Discrete and Continuous Dynamical Systems - Series B, 26(6), 3279-3302. https://doi.org/10.3934/dcdsb.2020232

Authors

Keywords

adaptive management, dynamic observer, input-to-state stability, Lur’e system, population ecology, positive system

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