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
    sub title: Convergence, Robustness and Applications
  name:
    name part: Chen, Yangquan.
    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: Wen, Changyun.
    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: xxk
    date issued: 1999
    edition: 1st ed. 1999.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 204 p. 2 illus. online resource.
  abstract: This book provides readers with a comprehensive coverage of iterative learning control. The book can be used as a text or reference for a course at graduate level and is also suitable for self-study and for industry-oriented courses of continuing education. Ranging from aerodynamic curve identification robotics to functional neuromuscular stimulation, Iterative Learning Control (ILC), started in the early 80s, is found to have wide applications in practice. Generally, a system under control may have uncertainties in its dynamic model and its environment. One attractive point in ILC lies in the utilisation of the system repetitiveness to reduce such uncertainties and in turn to improve the control performance by operating the system repeatedly. This monograph emphasises both theoretical and practical aspects of ILC. It provides some recent developments in ILC convergence and robustness analysis. The book also considers issues in ILC design. Several practical applications are presented to illustrate the effectiveness of ILC. The applied examples provided in this monograph are particularly beneficial to readers who wish to capitalise the system repetitiveness to improve system control performance.
  table of contents: High-order iterative learning control of uncertain nonlinear systems with state delays -- High-order P-type iterative learning controller using current iteration tracking error -- Iterative learning control for uncertain nonlinear discrete-time systems using current iteration tracking error -- Iterative learning control for uncertain nonlinear discrete-time feedback systems with saturation -- Initial state learning method for iterative learning control of uncertain time-varying systems -- High-order terminal iterative learning control with an application to a rapid thermal process for chemical vapor deposition -- Designing iterative learning controllers via noncausal filtering -- Practical iterative learning control using weighted local symmetrical double-integral -- Iterative learning identification with an application to aerodynamic drag coefficient curve extraction problem -- Iterative learning control of functional neuromuscular stimulation systems -- Conclusions and future research.
  note: by Yangquan Chen, Changyun Wen.
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Mechatronics
  subject:
    topic: Computational intelligence
  subject:
    topic: Control, Robotics, Mechatronics
  subject:
    topic: Computational Intelligence
  classification: TJ210.2-211.495
  classification: TJ163.12
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Control and Information Sciences, 248
  identifier: 9781846285394
  identifier: https://doi.org/10.1007/BFb0110114
  record info:
    record creation date: 121227
    record change date: 20191022082016.0
    record identifier: 978-1-84628-539-4