Model Predictive control

Model Predictive control

From power plants to sugar refining, model predictive control (MPC) schemes have established themselves as the preferred control strategies for a wide variety of processes. The second edition of Model Predictive Control provides a thorough introduction to theoretical and practical aspects of the mos...

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Detalles Bibliográficos
Autor Principal: Camacho, E. F.
Outros autores: Bordons Alba, Carlos (Directeur de la publication)
Formato: Livre numérique
Idioma:Anglais
Publicado: London : Springer London 2007.
Cham : Springer Nature
Series:Advanced Textbooks in Control and Signal Processing
Acceso en liña:Accès sur la plateforme de l'éditeur
Accès sur la plateforme de l'éditeur (Springer)
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Nota: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Model Predictive Control, Texte imprimé, 9780857293992
• Model Predictive Control, Texte imprimé, 9781852336943
Table des matières:
  • 1 Introduction to Model Predictive Control
  • 1.1 MPC Strategy
  • 1.2 Historical Perspective
  • 1.3 Industrial Technology
  • 1.4 Outline of the Chapters
  • 2 Model Predictive Controllers
  • 2.1 MPC Elements
  • 2.2 Review of Some MPC Algorithms
  • 2.3 State Space Formulation
  • 3 Commercial Model Predictive Control Schemes
  • 3.1 Dynamic Matrix Control
  • 3.2 Model Algorithmic Control
  • 3.3 Predictive Functional Control
  • 3.4 Case Study: A Water Heater
  • 3.5 Exercises
  • 4 Generalized Predictive Control
  • 4.1 Introduction
  • 4.2 Formulation of Generalized Predictive Control
  • 4.3 The Coloured Noise Case
  • 4.4 An Example
  • 4.5 Closed-Loop Relationships
  • 4.6 The Role of the T Polynomial
  • 4.7 The P Polynomial
  • 4.8 Consideration of Measurable Disturbances
  • 4.9 Use of a Different Predictor in GPC
  • 4.10 Constrained Receding Horizon Predictive Control
  • 4.11 Stable GPC
  • 4.12 Exercises
  • 5 Simple Implementation of GPC for Industrial Processes
  • 5.1 Plant Model
  • 5.2 The Dead Time Multiple of the Sampling Time Case
  • 5.3 The Dead Time Nonmultiple of the Sampling Time Case
  • 5.4 Integrating Processes
  • 5.5 Consideration of Ramp Setpoints
  • 5.6 Comparison with Standard GPC
  • 5.7 Stability Robustness Analysis
  • 5.8 Composition Control in an Evaporator
  • 5.9 Exercises
  • 6 Multivariable Model Predictive Control
  • 6.1 Derivation of Multivariable GPC
  • 6.2 Obtaining a Matrix Fraction Description
  • 6.3 State Space Formulation
  • 6.4 Case Study: Flight Control
  • 6.5 Convolution Models Formulation
  • 6.6 Case Study: Chemical Reactor
  • 6.7 Dead Time Problems
  • 6.8 Case Study: Distillation Column
  • 6.9 Multivariable MPC and Transmission Zeros
  • 6.10 Exercises
  • 7 Constrained Model Predictive Control
  • 7.1 Constraints and MPC

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