Process Modeling and Identification | AIChE

Process Modeling and Identification


Qin, S. J., The University of Texas at Austin

This session focuses on theoretical and application results in the area of process modeling and identification. Topics of interest include, but are not limited to: data-driven and theoretical modeling, novel identification algorithms, design of input signals, identification and validation under conditions of inadequate and/or incomplete data, and identification of nonlinear systems. Applications in nontraditional processes and systems are of particular interest.



Paper abstracts are public but to access Extended Abstracts, you must first purchase the conference proceedings.


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