|Teaching method||Contact hours|
|Course coordinator(s)||Prof. dr. ir. KJ Keesman|
|dr. ir. LG van Willigenburg|
|Lecturer(s)||dr. ir. LG van Willigenburg|
|Prof. dr. ir. KJ Keesman|
|Examiner(s)||dr. ir. LG van Willigenburg|
|Prof. dr. ir. KJ Keesman|
Language of instruction:
Assumed knowledge on:
BCT-20306 Modelling Dynamic Systems.
MAT-31806 Parameter Estimation and Model Structure Identification; MAT-26306 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. The optimal controller designs and their software implementation in a real-time controller will be tested on a computer and on a laboratory set-up.
After successful completion of this course students are expected to be able to:
- represent and analyze dynamic systems in state-space and in input-output form;
- design state observers;-design state feedback and dynamic output feedback controllers;
- recognize the importance of linearized models and quadratic criteria (LQ problems) for the design of Kalman filters and feedback controllers;
- apply solutions and algorithms for LQ problems;
- apply solutions and algorithms for the optimal control of non-linear systems;
- apply and evaluate the theory of optimal filtering and control in practice.
- self study to prepare for the lectures and practical assignments;
- lectures to provide some additional background material;
- computer exercises to apply the theory in a MATLAB environment;
- design and implementation of state observers and controllers on a laboratory set-up
three take home exams (individual); Note: for submission of take home exams see time schedule
report on practical experiment (groups of 2-3 persons)
two intermediate tests (individual)
report on practical experiment (couple)
The final mark consist of the average of the take home exams of Part I (30%), the intermediate tests of Part II (30%) and the practical reports, including observations during the experiments (40%).
The marks for the individual parts need to be ≥5.5. The mark for the exam will remain valid for 6 academic years.
The marks for the practical assignments and the case study will expire after one year.
Sheets/lecture notes + literature for further reading available in Brightspace.
|Restricted Optional for:||MBT||Biotechnology||MSc||D: Process Technology||5MO|
|MBT||Biotechnology||MSc||E: Environmental and Biobased Biotechnology||5MO|