Evaluation of Steady-State and Dynamic Soft Sensors for Industrial Crude Distillation Unit under Parametric Constraints

Abstract The parametric identification problem for industrial crude distillation unit (CDU) is considered. We take the a priori knowledge of the process into account by using a system of constraints for parameters of soft sensors models. The identification problem is transformed into a constrained optimization problem, which we solved using the active set method. The static and dynamic soft sensors are evaluated for industrial CDU located at JSC “Gazprom neftekhim Salavat” refinery. It was found that the model performed better when we used the proposed constrained optimization approach for identification instead of robust regression methods.