naa a22 4500 510821413 CHVBK 20180411083534.0 cr unu---uuuuu 180411e20130201xx s 000 0 eng 10.1007/s11814-012-0158-1 doi (NATIONALLICENCE)springer-10.1007/s11814-012-0158-1 A quasi-sequential parameter estimation for nonlinear dynamic systems based on multiple data profiles [Elektronische Daten] [Chao Zhao, Quoc Vu, Pu Li] A three-stage computation framework for solving parameter estimation problems for dynamic systems with multiple data profiles is developed. The dynamic parameter estimation problem is transformed into a nonlinear programming (NLP) problem by using collocation on finite elements. The model parameters to be estimated are treated in the upper stage by solving an NLP problem. The middle stage consists of multiple NLP problems nested in the upper stage, representing the data reconciliation step for each data profile. We use the quasi-sequential dynamic optimization approach to solve these problems. In the lower stage, the state variables and their gradients are evaluated through integrating the model equations. Since the second-order derivatives are not required in the computation framework this proposed method will be efficient for solving nonlinear dynamic parameter estimation problems. The computational results obtained on a parameter estimation problem for two CSTR models demonstrate the effectiveness of the proposed approach. Korean Institute of Chemical Engineers, Seoul, Korea, 2013 Dynamic Parameter Estimation Problem nationallicence Nonlinear Programming nationallicence Quasi-sequential Dynamic Optimization nationallicence Multiple Data Sets nationallicence CSTR nationallicence Zhao Chao College of Chemistry and Chemical Engineering, FuZhou University, 350108, FuZhou, P. R. China aut Vu Quoc Simulation and Optimal Processes Group, Institute of Automation and Systems Engineering, Ilmenau University of Technology, P. O. Box 100565, 98693, Ilmenau, Germany aut Li Pu Simulation and Optimal Processes Group, Institute of Automation and Systems Engineering, Ilmenau University of Technology, P. O. Box 100565, 98693, Ilmenau, Germany aut Korean Journal of Chemical Engineering Springer US; http://www.springer-ny.com 30/2(2013-02-01), 269-277 0256-1115 30:2<269 2013 30 11814 https://doi.org/10.1007/s11814-012-0158-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11814-012-0158-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhao Chao College of Chemistry and Chemical Engineering, FuZhou University, 350108, FuZhou, P. R. China aut NATIONALLICENCE 700 1- Vu Quoc Simulation and Optimal Processes Group, Institute of Automation and Systems Engineering, Ilmenau University of Technology, P. O. Box 100565, 98693, Ilmenau, Germany aut NATIONALLICENCE 700 1- Li Pu Simulation and Optimal Processes Group, Institute of Automation and Systems Engineering, Ilmenau University of Technology, P. O. Box 100565, 98693, Ilmenau, Germany aut NATIONALLICENCE 773 0- Korean Journal of Chemical Engineering Springer US; http://www.springer-ny.com 30/2(2013-02-01), 269-277 0256-1115 30:2<269 2013 30 11814 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer