Dynamic modeling, predictive control and performance monitoring : a data-driven subspace approach
著者
書誌事項
Dynamic modeling, predictive control and performance monitoring : a data-driven subspace approach
（Lecture notes in control and information sciences, 374）
Springer, c2008
大学図書館所蔵 件 / 全15件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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 predictor.
Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a "data-driven" approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.
目次
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.
「Nielsen BookData」 より