Title :
State estimation for batch distillation operations with a novel extended Kalman filter approach
Author :
Pan, Shuwen ; Su, Hongye ; Li, Pu ; Gu, Yong
Author_Institution :
Inst. of Cyber-Syst. & Control, Zhejiang Univ., Hangzhou, China
Abstract :
The composition and parameter estimation for batch distillation operations is addressed using a novel extended Kalman filter with unknown inputs without direct feedthrough (EKF-UI-WDF) approach. The major advantage of this approach lies in its capability of estimating states and unknown inputs (e.g. arbitrary deterministic disturbances) simultaneously, whereas the traditional nonlinear filter approaches cannot deal with this problem. As a result, this EKF-UI-WDF approach is able to provide on-line estimation of column compositions, flow rates and other parameters such as the tray efficiency in presence of unknown disturbances and noises. The restrictions of the EKF-UI-WDF are also remarked. Simulation results demonstrate the efficiency of this novel EKF approach comparing with other traditional nonlinear filters and indicate its potential of applications to other complex systems.
Keywords :
Kalman filters; batch processing (industrial); distillation; nonlinear filters; parameter estimation; state estimation; EKF-UI-WDF approach; batch distillation operation; column composition; extended Kalman filter approach; parameter estimation; state estimation; Automatic control; Constraint optimization; Filtering; Gaussian noise; Noise measurement; Nonlinear equations; Nonlinear filters; Parameter estimation; State estimation; Stochastic systems;
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2009.5400396