Estimation of Distillation Compositions Using Sensitivity Matrix Analysis and Kernel Ridge Regression
نویسندگان
چکیده
The stringent quality requirement of petroleum products in highly competitive markets makes on-line controlling of distillation composition essential. In this paper, a novel method using sensitivity matrix analysis and kernel ridge regression to implement on-line estimation of distillation compositions is proposed. In the approach, the sensitivity matrix analysis is presented to select the most suitable secondary variables to be used as the estimator’s inputs. The kernel ridge regression is used to build the composition estimator. The influence of measurement noise on the estimator’s performance is also investigated. Application to a simulated distillation column demonstrates the effectiveness of the method.
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