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:
    title: Design techniques for transient response control
  name:
    name part: Moore, Kevin Lane
    name part: 1960-
    role:
      role term: creator
  name:
    name part: Bhattacharyya, Shankar P.
    role:
      role term: degree supervisor.
  name:
    name part: Dahleh, Mohammed
    role:
      role term: degree supervisor.
  name:
    name part: Georghiades, Costas N.
    role:
      role term: degree committee member.
  name:
    name part: Hartfiel, Darald J.
    role:
      role term: degree committee member.
  name:
    name part: Howze, Jo W.
    role:
      role term: degree committee member.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1989
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: x, 152 leaves : illustrations ; 29 cm
  abstract: This dissertation analyzes and develops some design techniques for the control of transient response characteristics. First, a method for minimizing the output overshoot in SISO discrete-time systems with fixed-order controllers is given. The technique finds the optimal location of the assignable closed-loop system zeros for a given set of poles. Second, we investigate the use of multirate sampling techniques for assigning all the poles and zeros of the closed-loop system. Results are given for SISO plants, for square MIMO plants, and for the SISO servo problem. Intersample effects are also analyzed. Next, we consider a new approach called learning control. Learning control is an iterative approach to deriving the output of an optimal pre-filter, using actual input/output data. A complete analysis of the learning control problem is given for LTI systems, including a study of the nature of the solution, development of a learning controller based on parameter estimation, and a study of finite-horizon learning control schemes. We also present a learning control scheme that can be applied to a class of nonlinear systems which includes some models of robotic manipulators. Finally, we discuss the potential applications of artificial neural networks to the learning control problem.
  note: by Kevin Lane Moore.
  note: Typescript (photocopy).
  note: Vita.
  note: "Major subject: Electrical Engineering."
  note: Ph. D. Texas A & M University 1989
  note: Includes bibliographical references.
  subject:
    topic: Control theory
  subject:
    topic: Signal processing
    topic: Digital techniques
  subject:
    topic: Transients (Dynamics)
  subject:
    topic: Control theory
  subject:
    topic: Signal processing
    topic: Digital techniques
  subject:
    topic: Transients (Dynamics)
  subject:
    topic: Electrical Engineering
  identifier: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  record info:
    record content source: TXA
    record creation date: 900815
    record change date: 20200904152446.0
    record identifier: in00000919364
    language of cataloging:
      language term: eng