Fault tolerant model predictive controller; an application to an

industrial dearomatization process

Doctoral dissertation by

Markus Kettunen

Project description

• Duration: 04/2006-06/2010• Project funding: Academy of Finland• Project goals:

– Develop a data-based FTC strategy for countering the effects of faults in the control system sensors, analyzers and actuators

– Improve the performance and profitability of the industrial dearomatization process located at Neste Oil Naantali refinery, Finland

FTC

CV values, MV values, DV values, measurements

MPC

FDD

ProcessMV values

ReconstructedCVs, MVs & DVs

Fault information, correction values

CV values,MV values,DV values,

measurements

MPC structure

CV values,MV values,DV values,

measurements

Ut

Yt

Project results

• Improved control performance and quality of end products– Lower off-spec production– Lower energy consumption

• Enhanced profitability– Less than a year payback

period for the implementation of the FTC strategy to the target process