Process Design and Optimization (MLS-S03): Model Identification by Gradient Methods

This lecture describes the following topics: • Dynamic Models     - Conservation of Mass (Concentration Measurements)     - Conservation of Energy (Calorimetry)     - Beer’s Law (Spectroscopy) • Integration of Dynamic Models     - Euler’s Method     - Runge-Kutta’s Methods (RK) • Linear Regression Problems (OLS)     - Calibration-free Calorimetry and Spectroscopy • Gradient-based Nonlinear Regression Methods (NLR)     - Steepest Descent Method     - Newton-Raphson and Newton-Gauss Methods (NG)     - Newton-Gauss Levenberg Marquardt Method (NGLM) • References