BCT-31306 Systems and Control Theory


Credits 6.00

Teaching methodContact hours
Independent study
Course coordinator(s)Prof. dr. ir. KJ Keesman
dr. ir. LG van Willigenburg
Lecturer(s)Prof. dr. ir. KJ Keesman
dr. ir. LG van Willigenburg
Examiner(s)Prof. dr. ir. KJ Keesman
dr. ir. LG van Willigenburg

Language of instruction:


Assumed knowledge on:

BCT-20306 Modelling Dynamic Systems.

Continuation courses:

BCT-31806 Parameter Estimation and Model Structure Identification; BCT-21306 Control Engineering.


People want to be in control. In Wageningen most systems to be controlled are non-linear. Examples are chemical reactors, batch bioreactors , mechanical systems such as robots, climate control systems, environmental systems, but also management systems. This course teaches you how to optimally control such systems based on a mathematical model of the system in state-space form and a criterion reflecting the control objectives. Since the model is hardly ever a perfect description of reality, measurements will be used to improve the information concerning the state of the system. Retrieving this information is performed by so called state observers. Therefore the design and properties of state observers is another important subject considered in this course. Algorithms needed for the implementation of an optimal control strategy will also be presented..

Learning outcomes:

After successful completion of this course students are expected to be able to:
- represent and analyse dynamic systems in state-space and in input-output form;
- design state observers;
- apply the theory of optimal filtering and control in practice;
- reproduce the structure of an optimal control system consisting of an open loop and feedback part;
- specify common general control objectives mathematically using a cost function that is minimized;
- reproduce the necessary optimality conditions for open loop optimal control in terms of a two point boundary value problem that contains the cost function and the systems state-space model;
- understand the pros and cons of two types of algorithms to numerically solve optimal control problems;
- understandhow and why the linearization of a state-space model is employed for optimal feedback design.


- lectures;
- tutorials;
- computer exercises to apply the theory in a Matlab environment.


Observations during practicals. All practical reports are judged with a mark. Exam consist of the average of the take home exams (Part I, 30%) and intermediate tests (Part II, 30%) and the practical reports (40%) with scores of at least 5.5.


Course information, lecture notes and chapters from several well-known books on system and control theory will be available at the start of the course. The manuals for the computer exercises can be obtained during the lectures.

Restricted Optional for: MBTBiotechnologyMScD: Process Technology5MO
MBTBiotechnologyMScE: Environmental and Biobased Biotechnology5MO
MBEBiosystems EngineeringMSc5MO