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: Nonlinear Model Predictive Control
    sub title: Theory and Algorithms
  name:
    name part: Grüne, Lars.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Pannek, Jürgen.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 360 p. online resource.
  abstract: Nonlinear model predictive control (NMPC) is widely used in the process and chemical industries and increasingly for applications, such as those in the automotive industry, which use higher data sampling rates. Nonlinear Model Predictive Control is a thorough and rigorous introduction to NMPC for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB® and C++(downloadable from http://www.nmpc-book.com/ ) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. Nonlinear Model Predictive Control is primarily aimed at academic researchers and practitioners working in control and optimisation but the text is self-contained featuring background material on infinite-horizon optimal control and Lyapunov stability theory which makes the book accessible to graduate students of control engineering and applied mathematics.
  table of contents: Introduction -- Discrete-time and Sampled-data Systems -- Nonlinear Model Predictive Control -- Infinite-horizon Optimal Control -- Stability and Suboptimality Using Stabilizing Constraints -- Stability and Suboptimality without Stabilizing Constraints -- Feasibility and Robustness -- Numerical Discretization -- Numerical Optimal Control of Nonlinear Systems -- Examples -- Appendix: Brief Introduction to NMPC Software.
  note: by Lars Grüne, Jürgen Pannek.
  subject:
    topic: Engineering
  subject:
    topic: Chemical engineering
  subject:
    topic: System theory
  subject:
    topic: Automotive engineering
  subject:
    topic: Control engineering
  subject:
    topic: Engineering
  subject:
    topic: Control
  subject:
    topic: Systems Theory, Control
  subject:
    topic: Industrial Chemistry/Chemical Engineering
  subject:
    topic: Automotive Engineering
  classification: TJ212-225
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Communications and Control Engineering
  identifier: 9780857295019
  identifier: http://dx.doi.org/10.1007/978-0-85729-501-9
  record info:
    record creation date: 110408
    record change date: 20151030081442.0
    record identifier: 978-0-85729-501-9