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: Iterative Learning Control for Systems with Iteration-Varying Trial Lengths
    sub title: Synthesis and Analysis
  name:
    name part: Shen, Dong.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Li, Xuefang.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 256 p. 77 illus., 72 illus. in color. online resource.
  abstract: This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerous intuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.
  table of contents: Introduction -- Averaging and Expectation Techniques for Linear DT Systems -- Lifting Techniques for Linear DT Systems -- Moving Averaging Techniques for Linear DT Systems -- Switching System Techniques for Linear DT Systems -- Moving Averaging Tehcniques for Nonlinear CT Systems -- Modified Lambda-Norm Techniques for Nonlinear DT Systems -- Sampled-Data Control Techniques for Nonlinear CT Systems -- CEF Techniques for Parameterized Nonlinear CT Systems -- CEF Techniques for Nonparameterized Nonlinear CT Systems -- Summary and Future Research Directions -- Appendix.
  note: by Dong Shen, Xuefang Li.
  subject:
    topic: Control engineering
  subject:
    topic: System theory
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Algorithms
  subject:
    topic: Control and Systems Theory
  subject:
    topic: Systems Theory, Control
  subject:
    topic: Mathematical and Computational Engineering
  subject:
    topic: Algorithms
  classification: TJ212-225
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  identifier: 9789811361364
  identifier: https://doi.org/10.1007/978-981-13-6136-4
  record info:
    record creation date: 190129
    record change date: 20191022093049.0
    record identifier: 978-981-13-6136-4