Optimal Controllers for Stochastic Jump Processes.

Abstract

The report discusses the optimal feedback Bayes control, with memory, of a dynamic system governed by the statistics of any stochastic regular jump process. The latter is characterized in terms of the associated regular point process and the embedded state sequence. An optimality theorem, which gives a sufficient condition for an admissible control function to be optimal, is derived. A separation property, concerning the control and filtering operations, is established for the Bayes controller. The results are applied to derive optimal controllers for linear systems with random failures and renewals, assuming the latter to follow an alternating renewal point process model, or to be governed by a binary Markov process with unknown transition intensities. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1972
Accession Number
AD0756224

Entities

People

  • Izhak Rubin

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Data Science
  • Feedback
  • Filtration
  • Intensity
  • Linear Systems
  • Markov Processes
  • Mathematics
  • Sequences
  • Statistics
  • Transitions

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.