Course Objectives

To be able to design model-based control systems.

Course Description

Continuous-time and discrete-time state-space models. Discrete-time transfer function models. Estimation of transfer function models from logged data (time-series). Model-based tuning of PID controllers using simulators. Using state-estimators (softsensors), observer and7or Kalman-Filter, for control. Model-based Predictive Control (MPC).

Learning Methods

Lectures. Self-study. PC-based assignments. Projects (lab/simulation)

Assessment Methods

Projects and laboratory assignments counts 40%.
Individual final exam counts 60%

Minor adjustments may occur during the academic year, subject to the decision of the Dean