TY - GEN
T1 - A real-time approach for moving horizon estimation based nonlinear model predictive control of a fluid catalytic cracking unit
AU - Nagy, Z. K.
AU - Roman, R.
AU - Agachi, S. P.
AU - Allgoewer, F.
PY - 2005
Y1 - 2005
N2 - Output feedback non-linear model predictive control (NMPC) approach is illustrated on a simulated FCC unit (FCCU). This approach considers the most important features of a real-time control algorithm, which are often overlooked in simulation studies, contouring thus a framework for practical NMPC implementation. The most important features considered in the approach are: state and parameter estimation, efficient solution of the optimization, and computational delay. In the output feedback NMPC approach used, only measurements that are available in practice are considered, whereas the rest of the states are estimated together with uncertain model parameters using a moving horizon estimation (MHE) technique. The approach developed, is based on a state-of-the-art, large-scale SQP-type nonlinear optimization solver, which uses a sparse, interior-point multiple shooting algorithm, that exploits the special structure of optimization problem that arise in NMPC or MHE. The solution of the optimization problem from the NMPC and MHE requires a usually not negligible amount of time, when the system evolves to a different state where the solution is no longer optimal. The importance of taking this computational delay into account is also assessed and a real-time formulation of the control approach is described that includes the computational delay in the NMPC approach. The advantages of the proposed real-time approach are presented through the simulated industrial FCCU application. This is an abstract of a paper presented at the 7th World Congress of Chemical Engineering (Glasgow, Scotland 7/10-14/2005).
AB - Output feedback non-linear model predictive control (NMPC) approach is illustrated on a simulated FCC unit (FCCU). This approach considers the most important features of a real-time control algorithm, which are often overlooked in simulation studies, contouring thus a framework for practical NMPC implementation. The most important features considered in the approach are: state and parameter estimation, efficient solution of the optimization, and computational delay. In the output feedback NMPC approach used, only measurements that are available in practice are considered, whereas the rest of the states are estimated together with uncertain model parameters using a moving horizon estimation (MHE) technique. The approach developed, is based on a state-of-the-art, large-scale SQP-type nonlinear optimization solver, which uses a sparse, interior-point multiple shooting algorithm, that exploits the special structure of optimization problem that arise in NMPC or MHE. The solution of the optimization problem from the NMPC and MHE requires a usually not negligible amount of time, when the system evolves to a different state where the solution is no longer optimal. The importance of taking this computational delay into account is also assessed and a real-time formulation of the control approach is described that includes the computational delay in the NMPC approach. The advantages of the proposed real-time approach are presented through the simulated industrial FCCU application. This is an abstract of a paper presented at the 7th World Congress of Chemical Engineering (Glasgow, Scotland 7/10-14/2005).
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M3 - Conference contribution
AN - SCOPUS:33645157106
SN - 0852954948
SN - 9780852954942
T3 - 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering
SP - 504
BT - 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering - Congress Manuscripts
T2 - 7th World Congress of Chemical Engineering, GLASGOW2005, incorporating the 5th European Congress of Chemical Engineering
Y2 - 10 July 2005 through 14 July 2005
ER -