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...
保存先:
| 主要な著者: | , |
|---|---|
| 団体著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | English |
| 出版事項: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2012.
|
| 版: | 1st ed. 2012. |
| シリーズ: | Lecture Notes in Control and Information Sciences,
429 |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-642-28780-0 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
目次:
- 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.