Nonlinear data reconciliation with gross error detection and identification for steady-state and dynamic processes
Sensor measurements in a process network inherently contain random noise and/or gross errors. Thus, operational plant data should be pre-conditioned for process control, monitoring, and optimization. This work developed a strategy for nonlinear steady-state and nonlinear dynamic data reconciliation...
| 第一著者: | |
|---|---|
| その他の著者: | |
| フォーマット: | 学位論文 |
| 言語: | 英語 |
| 出版事項: |
Quezon City
College of Engineering, University of the Philippines Diliman
2015.
|
| 主題: | |
| オンライン･アクセス: | Abstract |