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...
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| Формат: | Диссертация |
| Язык: | English |
| Опубликовано: |
Quezon City
College of Engineering, University of the Philippines Diliman
2015.
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| Online-ссылка: | Abstract |