Title :
Improved disturbance estimation for dynamic matrix control
Author :
Lee, Kwangsoon ; Amirthalingam, Raja ; Yongho Lee ; Kwangsoon Lee
Author_Institution :
Dept. of Chem. Eng., Auburn Univ., AL, USA
Abstract :
We propose a method to use historical data to improve disturbance estimation in dynamic matrix control. It is proposed to compute the Kalman gain matrix of a step response model directly from plant data through a spectral or state-space realization. The Kalman filter can in turn be used to obtain an optimal prediction equation. The efficacy of the method is tested using a simulated heavy oil fractionator
Keywords :
Kalman filters; identification; matrix algebra; predictive control; state-space methods; step response; Kalman filter; Kalman gain matrix; disturbance estimation; dynamic matrix control; model predictive control; oil fractionator; state-space; step response; Chemical engineering; Data engineering; Equations; Feedback; Fractionation; Kalman filters; Petroleum; Predictive models; Stochastic processes; Testing;
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-4530-4
DOI :
10.1109/ACC.1998.688444
