Integration Project Systems and Control (SC42035)

Instructional objectives

After successfully completing the course, you should be able to:

• apply system and control theory to medium-complexity lab-scale and real-world processes,

• extrapolate the skills and knowledge gained to other, more complex problems,

• effectively use Matlab and Simulink for analysis, control design and related tasks,

• document the design process and its results in a high-standard technical report.

• present the results in a conference-type presentation.

The following methods and techniques will be applied to the lab setups:

• Mechanistic modeling based on Lagrange equations and mass balances.

• Implementation of a (nonlinear) mathematical model in Simulink.

• System identification and/or parameter estimation in order to calibrate the model, such that it can be used for model based control design and realistic simulations.

• Linearization and discretization of the model.

• Design of a linear Kalman filter (or a deterministic observer) for state estimation.

• Linear control design and performance analysis - apply at least two different methods, evaluate and compare their performance.

• System identification in closed loop - verify and possibly improve the accuracy of the model. This last item optional, though strongly recommended.