Nonlinear Estimation and Control of Particle Trajectories in the Ocean

Abstract

Our long-range goal is to develop optimization methods: 1) to estimate the physical state of the ocean in order to understand the present and future conditions and associated variability/uncertainty, and 2) to utilize such forecast information for control-decisions such as optimal drifter deployment strategy. This is being accomplished through the use of data assimilation methods for ocean circulation models and the study of extending the assimilation formulation to an optimal control problem.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2008
Accession Number
ADA533637

Entities

People

  • Ashwanth Srinivasan
  • Toshio M. Chin

Organizations

  • Rosenstiel School of Marine, Atmospheric, and Earth Science

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Atmospheric Sciences
  • Data Science
  • Deployment
  • Flow
  • Flow Fields
  • Information Science
  • Monte Carlo Method
  • Oceans
  • Particle Trajectories
  • Particles
  • Probability
  • Sequential Monte Carlo Methods
  • Simulations
  • Statistical Algorithms
  • Trajectories

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Robotics and Automation.