Course content

- First-principle modelling of physical-chemical-biological processes. - Transcription into the state-space and linearisation yielding the classical {A,B,C,D} representation: the Linear Time-Invariant System. - Laplace transform and transfer function matrix. Graphical representation as block diagrams and frequency plots with a focus on Bode plots. - Stability for LTI systems: eigenvalue / pole criterion, Nyquist and Routh criterion. - Simple graphical process identification of first-order plus dead-time systems. - Model simplification starting with higher-order transfer functions. - SISO pole-placement design (direct synthesis, IMC) yielding variations of PID controllers. - SIMC PID tuning - On-Off control. - Introduction to computer-controlled systems - Discrete version of PID with filter and anti-windup. - Aliasing and filtering. - Advanced subjects: selection of observability and controllability, similarity transformation, MIMO-systems relative gain array, decoupling, cascade control, feedforward control, selectors, model-predictive control and supervisory control.

Learning outcome

At the end of the course the students should: - Know the fundamentals of modelling and linearization of dynamic processes. - Know basic control theory. - Understand the power and limitations of the feedback principle. - Understand how instability can occur in dynamic systems. - Know how to develop simple dynamic process models. - Know how to tune PID controllers.

Learning methods and activities

Lectures, exercises, compulsory computing and laboratory exercises.

Compulsory assignments

• Exercises
• Lab
• Project

Recommended previous knowledge

Basic physics and process technology including differential equations.

Course materials

D.E. Seborg, T.F. Edgar, D.A. Mellichamp: Process Dynamics and Control, Wiley, 4th ed. Hand outs.

Credit reductions