Soft Sensor Based Predictive Control of Industrial Fluid Catalytic Cracking Processes

The operation of Fluid Catalytic Cracking (FCC) processes exhibits strongly nonlinear and highly interactive dynamic behaviour as well as having poorly understood reaction kinetics with many unmeasured operating variables which can play key roles in determining performance and give rise to difficult control problems. Soft sensors, which use easily measured and continuously available temperature, pressure and flowrate measurements, along with system models which make use of conservation equations to assimilate on-line learning parameters, are essential for advanced control. This article reports the application of a predictive control strategy using two soft sensors on an existing industrial FCC process. Both approaches resulted in improvements using this approach and the general issues are discussed in terms of generic procedures.

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