Parallel Implementations of Gradient Based Iterative Algorithms for a Class of Discrete Optimal Control Problems.

Abstract

This paper presents the parallel implementations of two iterative gradient based algorithms to solve the unconstrained linear quadratic regulator optimal control problem. It is shown that parallel evaluation of the step length and gradient of the quadratic cost function can be efficiently performed as a function of the number of processors. We then embed our parallel step length and gradient procedures to produce parallel implementations of the gradient and conjugate gradient methods that may be executed on an SIMD machine.

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Document Details

Document Type
Technical Report
Publication Date
Feb 28, 1987
Accession Number
ADA177792

Entities

People

  • Gerard G. Meyer
  • Louis J. Podrazik

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Counter IED
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computations
  • Computers
  • Dynamics
  • Iterations
  • Linear Systems
  • Mathematical Programming
  • New York
  • Parallel Computing
  • Parallel Processing
  • Parallel Processors
  • Steepest Descent Method

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Fluid Dynamics.
  • Parallel and Distributed Computing.