XWT-21305 Process Dynamics and Control (for Water Technology)

Course

Credits 5.00

Language of instruction:

English

Assumed knowledge on:

Differential equations, elementary matrix-vector calculus, process engineering; knowledge of classical control engineering is advantages but not required

Contents:

How can a water technological system be operated in a way that satisfies the user? This is the main question addressed in this course. We will start with introducing the powerful and general state space model representation as our main tool. Having the model, its behaviour can be analysed by analytical tools and by simulation. This guides the selection of sensors, actuators and sampling intervals. Next we need control. This requires specification of the objectives of the system. It is convenient to tackle the problem at various hierarchical levels governed by the time constants. At the fastest level the purpose is to create immunity against disturbances. We will examine the tuning of low level controllers, and will find out about stability and robustness. At the next level, multi-variable control tackles the problem of interaction. Finally, there is a supervisory level, where the task is to achieve the overall best performance, according to user defined goals of robustness, safety and economy. Dynamic optimization is the most powerful technique for this. The knowledge gained cannot only be used for system operation, but also to discover bottlenecks in the design.

Learning outcomes:

At the end of the course, the student is expected to:
- be able to specify user relevant goals for the operation of a water technological system
- be able to model the system in state-space form;
- have knowledge on hierarchical decomposition of system operation;
- know how to tune elementary basic low level controllers;
- be able to use the model to analyse the dynamical behaviour and to find time constants, and apply them for monitoring and control assessment;
- know how to develop multivariable predictive controllers based on user set objectives;
- know how to achieve user-defined optimum performance, respecting constraints;
- be able to simulate a controlled system and judge its performance;
- be able to recommend design changes on the basis of operability bottlenecks.

Activities:

- attending lectures and instruction hours;
- studying the presented material and hand-out;
- preparing and performing computer exercises;
- exercise homework assignments;
- preparing and executing a real experiment.

Examination:

- take home exams;
- assignments in groups of two persons.

Literature:

Lecture notes.