Final Report: 3.4.1 Rare Events, Control and Metastability of Weakly Interacting Particle Systems

Abstract

Many engineering systems can be modeled as a large collection of stochastically evolving particles, whose dynamics are weakly coupled by an interaction that depends only on the empirical distribution of the particles. Good design of these systems requires accurate estimation of key performance measures of interest, such as the expected exit time from the neighborhood of a desirable operating point. This requires an understanding of stability, mestastability and other related aspects of the long-time behavior of the system. The focus of this proposal is to develop general analytical and computational methods for quantitative characterizations of these properties. The techniques developed will include partial differential equation characterizations and control representations for the construction of Lyapunov functions, formulation and solution of optimization problems that identify the most likely large way in which certain rare events of interest occur and the development of efficient importance sampling algorithms for accurate estimation the probabilities of rare events of interest. Additionally, these methods developed will be applied to shed insight into the performance and design of real-world systems.

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Document Details

Document Type
Technical Report
Publication Date
Aug 29, 2016
Accession Number
AD1058201

Entities

People

  • Kavita Ramanan
  • Paul Dupuis

Organizations

  • Brown University

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Differential Equations
  • Dynamics
  • Engineering
  • Equations
  • Lyapunov Functions
  • Markov Chains
  • Markov Processes
  • Mathematics
  • Metastable State
  • Numerical Analysis
  • Partial Differential Equations
  • Probability
  • Stochastic Processes
  • Students
  • Throughput

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Materials Science and Engineering.
  • Systems Analysis and Design