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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| Main Authors: | , |
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| 企業作者: | |
| 格式: | 電子 電子書 |
| 語言: | English |
| 出版: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2012.
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| 版: | 1st ed. 2012. |
| 叢編: | Lecture Notes in Control and Information Sciences,
429 |
| 主題: | |
| 在線閱讀: | https://doi.org/10.1007/978-3-642-28780-0 |
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書本目錄:
- 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.