Evaluation study of an efficient output feedback nonlinear model predictive control for temperature tracking in an industrial batch reactor

摘要: The paper illustrates the benefits of nonlinear model predictive control (NMPC) for setpoint tracking an industrial batch polymerization reactor. Real-time feasibility on-line optimization problem from NMPC is achieved using efficient multiple shooting algorithm. A real-time formulation that takes computational delay into account described. relevant derived complex-first principles and fitted to experimental data maximum likelihood estimation. parameter adaptive extended Kalman filter (PAEKF) used state estimation adaptation. performance implementation assessed via simulation results.