19. Effect of POE Reducing POM improves performance TSS = 240 sec MCF = 0.75 ROT = 0.05 Case POM "Lambda" Max CV Overshoot Max MV Move Apparent TSS min % % min 1 22 6 1.17 1.82 21 2 39.5 9 2.19 5.64 44 3 55.5 11 2.76 4.44 44
20. Effect of Model Correction Factor TSS = 240 sec POM = 39.5 ROT = 0.05 Case MCF "Lambda" Max CV Overshoot Max MV Move Apparent TSS min % % min 1 0.5 5 2.11 5.63 33 2 0.75 9 2.19 5.64 44 3 0.9 8 2.12 5.45 32.5
21. Effect of Rotation Factor Case ROT "Lambda" Max CV Overshoot Max MV Move Apparent TSS min % % min 1 0.01 8 2.22 5.78 44 2 0.05 9 2.19 5.64 44 3 0.1 8 2.18 5.65 32.5 4 0.5 8 2.11 5.47 33 TSS = 240 sec POM = 39.5 MCF = 0.75
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Hinweis der Redaktion
Main Points: A basic concept of Model Predictive Control is that the control predicts future process behavior based on past process input changes. MPC predicts future behavior based on step response models.
Main Points: For multivariable control problems, a matrix of control models is used to calculate the response of each controlled and constraint variable based on changes to manipulated variables or measured disturbance variables. This is where the term Dynamic Matrix Control come from. Transition: Once you have defined your manipulated variables and control variables, its easy to configure DeltaV Predict using standard DeltaV Control Studio.