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...
Gorde:
| Egile Nagusiak: | , |
|---|---|
| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2012.
Cham : Springer Nature |
| Saila: | Lecture Notes in Control and Information Sciences
429 |
| Sarrera elektronikoa: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Oharra: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Explicit Nonlinear Model Predictive Control, Texte imprimé, 9783642287817 • Explicit Nonlinear Model Predictive Control, Texte imprimé, 9783642287794 |
Aurkibidea:
- 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.