(57b) Non-Traditional Model Predictive Control and Nonlinear Process Modeling for Return on Investment APC Projects | AIChE

(57b) Non-Traditional Model Predictive Control and Nonlinear Process Modeling for Return on Investment APC Projects

As Advanced Control technologies find broader and broader users in industrial automation and control, there are challenges on what to do when processes are sometimes not fully continuous.

For example gas processing plants in the field which face huge condensate feed surges known as pigging come from varying conditions in the gas reservoir or the gas and condensate collection system. In addition, there a major production lines that are not continuous but have start/stop operations for clean-in-place and to respond to feed availability changes. These production plants have to have well designed MPC improve process predictability and stability during these transitions.

Handling major process changes or transitions become critical to maximize the return on investment of the advanced control strategy. Success then   becomes a sifnficant differentiator from traditional continuous control strategies. This paper addresses new advances in gas processing controls of fractionation, cryogenic processes and even production lines that periodically start and stop and highlights the challenges and methods in the industrial process control practice.

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