Dynamic Modeling, Predictive Control and Performance Monitoring A Data-driven Subspace Approach /
A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the p...
| Main Authors: | , |
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| Corporate Author: | |
| Language: | English |
| Published: |
London :
Springer London : Imprint: Springer,
2008.
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| Edition: | 1st ed. 2008. |
| Series: | Lecture Notes in Control and Information Sciences,
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-1-84800-233-3 |
Table of Contents:
- I Dynamic Modeling through Subspace Identification
- System Identification: Conventional Approach
- Open-loop Subspace Identification
- Closed-loop Subspace Identification
- Identification of Dynamic Matrix and Noise Model Using Closed-loop Data
- II Predictive Control
- Model Predictive Control: Conventional Approach
- Data-driven Subspace Approach to Predictive Control
- III Control Performance Monitoring
- Control Loop Performance Assessment: Conventional Approach
- State-of-the-art MPC Performance Monitoring
- Subspace Approach to MIMO Feedback Control Performance Assessment
- Prediction Error Approach to Feedback Control Performance Assessment
- Performance Assessment with LQG-benchmark from Closed-loop Data.