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Explicit Nonlinear Model Predictive Control Theory and Applications

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time...

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Bibliographic Details
Main Authors: Grancharova, Alexandra, Johansen, Tor Arne (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2012, 2012
Edition:1st ed. 2012
Series:Lecture Notes in Control and Information Sciences
Subjects:
Nonlinear Optics
Applied Dynamical Systems
Control And Systems Theory
Control Theory
Systems Theory, Control
System Theory
Nonlinear Theories
Control Engineering
Dynamics
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Multi-parametric Programming
  • Nonlinear Model Predictive Control
  • Explicit NMPC Using mp-QP Approximations of mp-NLP
  • Explicit NMPC via Approximate mp-NLP
  • Explicit MPC of Constrained Nonlinear Systems with Quantized Inputs
  • Explicit Min-Max MPC of Constrained Nonlinear Systems with Bounded Uncertainties
  • Explicit Stochastic NMPC
  • Explicit NMPC Based on Neural Network Models
  • Semi-Explicit Distributed NMPC.

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