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Chapter 6: Steady-State Data Reconciliation with Model Uncertainties

Chapter 6: Steady-State Data Reconciliation with Model Uncertainties. Generated noise vectors. Calculated model errors.  = f ( y , z ). Calculate V(  1 ), V(  2 ), Cov( 1 ,  1 ), ……. (6.5). (6.6). FI. FI. FI. FI. FI. FI. CWR. CWS. 3. 5. 6. 1. 2. 4. Figure 1.3.

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Chapter 6: Steady-State Data Reconciliation with Model Uncertainties

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  1. Chapter 6:Steady-State Data Reconciliation with Model Uncertainties

  2. Generated noise vectors Calculated model errors  = f(y, z) Calculate V(1), V(2), Cov(1, 1), ……

  3. (6.5)

  4. (6.6)

  5. FI FI FI FI FI FI CWR CWS 3 5 6 1 2 4 Figure 1.3

  6. Variance of models Reconciled data Raw measurements Reconciled by exact models

  7. Chapter 7:Dynamic Data Reconciliation

  8. Filtering t Data used for estimation Prediction Data used for estimation Smoothing Data used for estimation

  9. Moving window 0 tp Time Window width=10

  10. (7.2)

  11. (7.4)

  12. Digital Controllers Reconciled data Dynamic Data Reconciliation Controlled variables Manipulated variables Raw measurements Process Control Valve Noise

  13. LC FI Feed Outlet

  14. (7.6)

  15. (7.7)

  16. (7.8) (7.9) (7.10)

  17. (7.11) (7.12)

  18. (7.13) (7.14)

  19. (7.15) (7.16)

  20. A guess of an initial value convergence

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