# Education
**Source**: https://www.tudelft.nl/lr/organisatie/afdelingen/control-and-operations/control-and-simulation/education
**Parent**: https://www.tudelft.nl/lr/organisatie/afdelingen/control-and-operations/control-and-simulation
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# Education
### Control and Simulation Profile
The C&S profile focuses on design, analysis and testing of automatic and manual guidance, navigation, and control (GNC) systems for aerospace applications. Our aim is to enhance safety, sustainability, and performance of aerospace vehicles by creating better interfaces, procedures, and automation. The profile builds on systems and control theory, stochastic dynamic systems and signals, flight simulation, and modelling human cognition and manual control. Students can work with state-of-the-art facilities to close the loop of theory and application, using the laboratory aircraft, the SIMONA flight simulator, the ATC lab, the HMI-lab, or the CyberZoo indoor flight-test area. For their electives and thesis, students can choose from among three research and education clusters: 1) Guidance, Navigation and Control, 2) Micro Aerial Vehicles, or 3) Human Machine Systems.
For **[Guidance, Navigation and Control](https://www.tudelft.nl/lr/organisatie/afdelingen/control-and-operations/control-and-simulation/research/aerospace-guidance-navigation-and-control)**, students can focus on the design of highly automated, intelligent and (semi-)autonomous aerial vehicles. They can learn advanced control theory, global optimization approaches, state and parameter estimation techniques, and modern dynamic modelling techniques. Aeronautical research examples are fault tolerant and re-configurable flight control, flight envelope clearance and protection, vehicle dynamics model identification, and advanced flight test instrumentation systems. Space examples are rendezvous/docking vehicle control, GNC for formation flying spacecraft, modelling of spacecraft with flexible structures and liquid sloshing, and optimal terminal area energy management of re-entry vehicles.
The **[Micro Aerial Vehicle (MAV)](https://www.tudelft.nl/lr/organisatie/afdelingen/control-and-operations/control-and-simulation/research/micro-aerial-vehicle-lab)** research and education is a multi-disciplinary field, combining flight dynamics and control of innovative flying vehicles, obstacle avoidance with computer vision and machine learning, interaction with the environment and swarming. Students are encouraged to apply theory to real flying vehicles and perform flight test experiments. Example research projects are drone racing through machine learning, spiking neural networks for obstacle avoidance and control, flight control of hybrid VTOL drones, and drones with a sense of touch.
For **[**Human-Machine Systems**](https://www.tudelft.nl/lr/organisatie/afdelingen/control-and-operations/control-and-simulation/research/aerospace-human-machine-systems)**, students will learn to understand, model and support human manual and supervisory control behavior, focusing on perception and skill-based control behavior, using modern identification techniques and classical control, toward cognitive control behavior involved in supervising highly automated systems. Research examples are the design of haptic force-feedback systems for aerospace (and other) vehicles, modelling human visual-vestibular perception and control, neuromuscular system dynamics and biodynamic coupling effects, the optimal tuning of flight simulator visual and motion cues, aircraft handling qualities and advanced fly-by-wire systems, 3D flight guidance displays, tele-operation of unmanned aerial vehicles, advanced decision-support systems, and human-autonomy teaming.
### The C&S learning objectives are:
1. Knowledge of modern methods for analysis of control problems and synthesis of control systems.
2. Knowledge of modelling and supporting human manual and supervisory control behavior, including modern methods for identification and interface design frameworks.
3. Skills in the use of modern control and simulation programs.
4. Skills in programming, setup, and execution of simulator experiments or test flight experiments.
5. Insight into related disciplines such as artificial intelligence, statistics, sensor fusion, distributed computing, fast-time and real-time simulation, interface design.
For the course descriptions see the [digital study guide](https://studyguide.tudelft.nl/a101_displayProgram.do?program_tree_id=31379).
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