Program Overview

Programme Overview

The Systems and Control (MSc) programme at the University of Twente is designed to provide students with a comprehensive understanding of systems and control theory. The programme is structured into two years, with the first year consisting of compulsory courses, profile-specific courses, and electives. The second year focuses on practical work, including an internship and a graduation project.

Programme Structure

The programme is divided into several components:

• Core programme: 30 credits
• Profile-specific and elective subjects: 30 credits
• Internship/Graduation Project: 60 credits

Core Programme

The core programme consists of the following courses:

1. Control System Design for Robotics (5 EC)
2. Perspectives on Engineering Design (2.5 EC)
3. Philosophy of Engineering: Ethics (2.5 EC)
4. System Identification with Parameter Estimation and Machine Learning (5 EC)
5. Integration Project (5 EC)
6. Modelling and Simulation (5 EC) or Modelling, Dynamics, and Kinematics (5 EC)

Specialisations and Specialisation-Linked Subjects

The programme offers four specialisations:

1. Robotics and Mechatronics
2. Control Theory
3. Bio-mechatronics
4. Unmanned Aerial Vehicles

Each specialisation has a set of linked courses that students can choose from. The total course programme of 60 credits must be approved by the Examination Board.

List of Specialisation-Linked and Elective Courses

The following courses are available:

• Engineering Acoustics (5 EC)
• Image Processing and Computer Vision (5 EC)
• Machine Learning I (5 EC)
• Measurement Systems for Mechatronics (5 EC)
• Modelling, Dynamics & Kinematics (5 EC)
• Systems and Control (6 EC)
• Systems Engineering (5 EC)
• Transducer Science (5 EC)
• Aerodynamics and Flight Dynamics (5 EC)
• Deep Learning - From Theory to Practice (5 EC)
• Electric Vehicle System Design (5 EC)
• Flexible Multibody Dynamics (5 EC)
• Learning and adaptive control (5 EC)
• Machine Learning II (5 EC)
• Optimal Control (5 EC)
• Robot Perception, Cognition, and Navigation (5 EC)
• Robotics for Medical Applications (5 EC)
• Advanced Software Development for Robotics (5 EC)
• Design Principles for Robotic and Mechatronic Mechanisms (5 EC)
• Human movement control (5 EC)
• Machine learning in engineering (5 EC)
• Nonlinear Control (5 EC)
• Optimal Estimation for Dynamic Systems (5 EC)
• Random Signals and Filtering (5 EC)
• Regulating robotics and drones (2.5 EC)
• Robust Control (5 EC)
• Software Development for Robotics (5 EC)
• Tele-presence in Robotics (5 EC)
• AI for Autonomous Robots: deep learning and reinforcement learning (5 EC)
• Airborne Laser Scanning (5 EC)
• Biomechatronics (5 EC)
• Control for UAVs (5 EC)
• Embedded Systems Laboratory (5 EC)
• Identification of Human Physiological Systems (5 EC)
• Introduction to Robotics Design (5 EC)
• Time Series Analysis (5 EC)

• Machine Learning I, AI for Autonomous Robots: deep learning and reinforcement learning, and Machine learning in engineering
• Control System Design for Robotics, Control for (B)ME, Advanced Control Engineering, and Systems and Control
• Time Series Analysis and System Identification with Parameter Estimation and Machine Learning

Programme Requirements

Students must complete the core programme, profile-specific courses, and electives, and participate in an internship and a graduation project. The total course programme must be approved by the Examination Board.