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: Identification of Dynamic Systems
    sub title: An Introduction with Applications
  name:
    name part: Isermann, Rolf.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Münchhof, Marco.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXV, 705 p. online resource.
  abstract: Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators, machine tools, industrial robots, pumps, vehicles to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the nonparametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
  note: by Rolf Isermann, Marco Münchhof.
  subject:
    topic: Engineering
  subject:
    topic: Computer simulation
  subject:
    topic: Calculus of variations
  subject:
    topic: Physics
  subject:
    topic: Complexity, Computational
  subject:
    topic: Engineering
  subject:
    topic: Complexity
  subject:
    topic: Calculus of Variations and Optimal Control; Optimization
  subject:
    topic: Simulation and Modeling
  subject:
    topic: Numerical and Computational Physics
  classification: QA76.9.M35
  classification: 620
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783540788799
  identifier: http://dx.doi.org/10.1007/978-3-540-78879-9
  record info:
    record creation date: 101120
    record change date: 20151204164043.0
    record identifier: 978-3-540-78879-9