Robust set-point optimization of inferential control system of crude oil distillation units.

Abstract

Abstract The changes in the characteristics of the crude oil feed to an atmospheric distillation unit can influence the quality of the products. Also, the crude flow rate disturbances should be handled efficiently. An inferential control structure is adopted using RGA analysis where multiple tray temperatures are controlled. Then, a closed-loop stochastic optimization framework is proposed for tighter control and set of the decision variables is extended using the set-points of the decentralized PI controllers. The closed-loop simulations show improved disturbance rejection performance of the controllers against disturbances of feed flow rate and quality as well. Also, the challenges regarding the specifications of the product quality expressed as equality constraints are addressed. Both single and joint constraints cases are discussed.