Improved Chemical Process Operations through Data-Based

Improved Chemical Process Operations through Data-Based Disturbance Models Eastman gas-phase reactor control system Model Predictive Controller

csp

Identify the minimum number of disturbances from data

∆T Fi

FC

u

To

Ti

x + = Ax + Bu + Gw y = Cx + v w ∼ N(0, Q) v ∼ N(0, R)

Minimum variance estimate of G

c

Convex semidefinite optimization

Gas-phase Reactor

Impose positive definite constraints on variances Q, R Implemented on data from Eastman (above and right) and ExxonMobil Extending to nonlinear models Using with other state estimation methods (particle filtering)

J.B. Rawlings (U. Wisconsin)

p(Y) p(Y)

90

9000

45

4500

0.25

0 −0.25 YC

0

0Y

T

0.25 −0.25

Using original covariances

0.025

0 −0.025 YC

0

0Y

T

−0.025 0.025

Using ALS covariances

2006

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