Process Models & Parameter Identification

This lecture covers the goals of calibrating models using measurements, virtual sensors, data reconciliation, and parameter identification in process models. It explains how to define the level of detail in unit models, the importance of values of parameters, and the process of measurement and parameter identification. The lecture also discusses the heat exchanger example, equations, state variables, and degrees of freedom analysis. It delves into characterizing industrial processes, energy conversion systems, and the structural analysis of rearranging matrices. Additionally, it presents examples of simplified systems, incidence matrix analysis, and the importance of choosing good measures in industrial processes.