rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: weighted residual framework for formulation and analysis of direct transcription methods for optimal control
  name:
    name part: Singh, Baljeet.
    role:
      role term: creator
  name:
    name part: Bhattacharya, Raktim
    role:
      role term: thesis advisor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: In the past three decades, numerous methods have been proposed to transcribe optimal control problems (OCP) into nonlinear programming problems (NLP). In this dissertation work, a unifying weighted residual framework is developed under which most of the existing transcription methods can be derived by judiciously choosing test and trial functions. This greatly simplifies the derivation of optimality conditions and costate estimation results for direct transcription methods. Under the same framework, three new transcription methods are devised which are particularly suitable for implementation in an adaptive refinement setting. The method of Hilbert space projection, the least square method for optimal control and generalized moment method for optimal control are developed and their optimality conditions are derived. It is shown that under a set of equivalence conditions, costates can be estimated from the Lagrange multipliers of the associated NLP for all three methods. Numerical implementation of these methods is described using B-Splines and global interpolating polynomials as approximating functions. It is shown that the existing pseudospectral methods for optimal control can be formulated and analyzed under the proposed weighted residual framework. Performance of Legendre, Gauss and Radau pseudospectral methods is compared with the methods proposed in this research. Based on the variational analysis of first-order optimality conditions for the optimal control problem, an posteriori error estimation procedure is developed. Using these error estimates, an h-adaptive scheme is outlined for the implementation of least square method in an adaptive manner. A time-scaling technique is described to handle problems with discontinuous control or multiple phases. Several real-life examples were solved to show the efficacy of the h-adaptive and time-scaling algorithm.
  note: by Baljeet Singh.
  note: "Major Subject: Aerospace Engineering"
  note: Electronic resource.
  note: Doctor of Philosophy Texas A&M University 2010 http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8688
  note: Includes bibliographical references.
  note: Text (Dissertation)
  subject:
    topic: Major Aerospace Engineering
  subject:
    topic: Trajectory optimization
  subject:
    topic: Optimal control
  subject:
    topic: Pseudospectral methods
  identifier: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8688
  record info:
    record content source: TXA
    record creation date: 120306
    record change date: 20151202151700.0
    record identifier: in00002746694