|Teaching method||Contact hours|
|Excursion (one day)||8|
|Course coordinator(s)||dr. ir. S van Mourik|
|Lecturer(s)||MSc D. Reyes Lastiri|
|dr. RJC van Ooteghem|
|dr. ir. S van Mourik|
|Examiner(s)||dr. ir. S van Mourik|
|dr. RJC van Ooteghem|
Language of instruction:
Assumed knowledge on:
FTE-34806 Modeling of Biobased Production Systems, MAT-26306 Control Engineering, MAT-26806 Data Analysis Biosystems Engineering, Matlab (basics)
Sustainable food production systems aim at reaching high production with reduced costs and labour, a lower environmental impact and use of resources, and higher animal welfare.
Precision farming aims at sustainable food production by managing materials and resources in time and space. It ranges from field and barn level up to individual plants and animals. Precision farming covers three aspects: sensing, decision-making, and actuation. These aspects form a continuous control loop that describe the behaviour and performance of the system.
In this course, students learn to apply principles of control engineering to (grey box) mathematical models with the objective of providing resources (materials and energy) at the time and place where they are required in a farming system, and with the right dosage.
Students look into current challenges and possible solutions for relevant farming examples.
The following topics will be addressed during the course:
- concepts and example applications of precision farming in various agriculture domains, as well as current practical issues;
- update on sensing, modelling, and control (assumed knowledge);
- analysis of various errors (e.g. sensor and model errors), and of methods that can solve this problem;
- various control methods, ranging from data based PID controllers to model-based control with integration of sensor data.
The course consists of lectures covering the required theory, with written exercises to apply the acquired knowledge. The contents are then implemented into a graphical simulator during computer practical sessions. Finally, students integrate the course contents into a comprehensive simulation project.
After successful completion of this course students are expected to be able to:
- identify bottlenecks of basic control engineering techniques on precision farming systems;
- apply specialized control methods to solve bottlenecks;
- apply control strategies that take into account future events;
- define an appropriate control objective (e.g. to maximize benefits and minimize resources);
- identify sources of uncertainty and represent them mathematically;
- define and compare management strategies to deal with uncertainties and disturbances in the system;
- design precision control strategies to meet individual requirements (e.g. of animals / patches of land with different characteristics);
- combine strategies of control with uncertainty propagation to assess performance and risks.
- pen-and-paper exercises;
- computer exercises
- project work;
The final grade will be determined by the written exam grade (50%), the project grade (30%, based on report and code), and the grades of the assignments (20%). A minimum grade of 5.50 is required for the exam and the project. The assignments are individual, and are graded on a trinary basis (good-pass-fail). During the project days, you work in pairs. Both project partners will obtain the same grade for their project report. On these project days, attendance is obligatory. At the end of each project day, some students may be asked to give a short presentation.
Study materials from previous courses will be used. Other materials may be provide:
- Dorf & Bishop – Modern Control Systems (11th edition)
- Additional precision farming journal papers (will be provided)
|Restricted Optional for:||MBE||Biosystems Engineering||MSc||5MO|