Are you looking for an Internship in Control Systems? We have compiled the following updated (May 2017) list of topics for you, please contact the intended supervisors if you are interested:

Implementation of Model-Driven Electricity Load Forecasting Algorithm in JAVA

This traineeship consists of two tasks: the first amounts to converting a probabilistic load forecasting algorithm that has been developed in Matlab to Java. The second task amounts to comparing the forecasting accuracy of this algorithm
with an existing algorithm that has been developed with Enexis. It is pointed out that Enexis pays for the completion of the first task. Requirement: Good experience with JAVA programing. Read more...

Contact: Prof.dr. S. Weiland

Modelling smart battery charger system

NXP Semiconductors ( a large and international semiconductor company that delivers Integrated Circuits (ICs) for a wide range of applications ranging from mobile (mobile phones) and security-based (banking cards, etc) applications to automotive applications (sensors, communication, microcontrollers). Read more...

Contact: H.J. Bergveld

Relaxor ferroelectric piezoelectric and electrostrictive materials

In a lithographic machine many elements are moved with piezoelectric actuators. Advantages of these actuators are their compactness, accuracy and fast response. Major drawbacks are the limited actuation stroke and non-linear (hysteretic) behavior. Read more...

Contact: Butler

Application Support Engineer Intern at MathWorks Eindhoven

During your internship at the MathWorks, which was voted the 6th best Technical Company to work by Glassdoor, you will be working from the Eindhoven office with MATLAB and Simulink every day. The goal will be for you to do 2 things: 

  • Design, create and update an eye catching technical demonstration with Hardware that illustrates the value the MathWorks toolchain that can be leveraged at tradeshows by the MathWorks sales team. Today it is possible to generate code from Simulink to change the control strategy on the AR Drone 2.0. We would like you to have the Drone follow a green ball automatically.
  • Work with MATLAB as a data analytics platform helping further develop internal reporting tools

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Contact: G. Thomas, M.Sc. ( and R. Tóth (

Extreme Accurate Piezo Strain-sensor

In a lithographic machine accurate positioning of the wafer, on the wafer stage, is critical. The rigid-body motion of this stage is measured by encoders or an interferometer system. But next to this rigid-body mode, also flexible (deformation) modes play a role. Read more...

Contact: H. Butler

Linear Parameter Varying (LPV) modeling of a vehicle in free flight

To improve the estimated aerodynamic coefficients based on free flight data, the proposed approach aims at constructing a Linear Parameter-Varying (LPV) model derived from the known nonlinear equations describing the behavior of a vehicle in free flight. In that direction, the objective of the internship is to investigate the existing linearization methods in order to select the best suited to the construction of the LPV model. This model will be implemented in a MATLAB/ Simulink environment and can be tested and validated using the measured signals of different architectures as re-entry space vehicles or projectiles.

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Contact: R. Tóth (

3D Food Printing

TNO has been active in the area of 3D printing for over 20 years. Initially 3D printing was used for technical applications (general prototyping, aerospace & automotive engineering) and employed a limited set of materials, typically various types of plastics and metals.
3D printing, however, is finding its way into new areas and over the past 5-6 years TNO has become the world leader in the area of 3D food printing. Food printing not only enables the creation of novel products with interesting shapes, but it also allows the creation of fully personalized nutrition or the creation of novel (micro)structures that can lead to new food textures and food experiences.

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Contact : Prof. dr. S. Weiland

Experimental Validation and Comparison of State-of-Charge and Temperature-estimation Algorithms for Li-ion Batteries

 Li-ion battery technology is, due to properties such as high energy density, a growing and very promising technology for enabling and accelerating many sustainable and renewable solutions in society, such as energy storage and sustainable transport. For safe and proper operation of Li-ion batteries, estimation of the battery State-of-Charge (SoC) and Temperature (T) is needed. This project aims at implementing, experimentally validating and comparing existing SoC and T-estimation algorithms using the battery test setup at the Control-Systems lab. Moreover, this is the first opportunity to test a new T-estimation algorithm which does not need temperature sensors, but uses impedance measurements for retrieving the battery temperature.
Supervisors: Henrik Beelen, Tijs Donkers

Contact: T. Donkers

Improved battery management in small-sized Li-ion battery packs

Cleantron is a battery-pack manufacturer located in Nieuw Vennep, near Schiphol, the Netherlands ( Main applications that packs are designed for are e-mobility (scooters, light electrical vehicles), healthcare (electrical wheelchairs, small carts), industrial equipment (e.g. cleaning machines) and solar off-grid storage batteries. Pack voltages are usually 24V or 48V. Cleantron has the desire to improve battery management by using individual cell measurements inside the pack, including also cell impedance measurements. At the TU/e, we have a research programme running on battery management, where based on measured battery voltage, current, impedance and outside temperature the internal states, including the internal temperature based on the measured impedance, are derived. This internship builds on two earlier TU/e CS internships at Cleantron and aims at implementing our latest state and temperature estimation algorithms in an actual microcontroller inside the pack, using new cell-based electronics that also assess the cell impedance.

Supervisors: Maurice van Giezen, Maarten Kelder (Cleantron), Henk Jan Bergveld

Contact: H.J. Bergveld