Research
Reaching for ever-increasing levels of safety, efficiency and capacity of aerospace will require developing more capable automatic control systems in terms of adaptability and autonomy, and more advanced human-machine systems to interact with them. The section Control and Simulation (C&S) aims to advance the development of such systems, building on a solid theoretical basis and physical insights while exploiting theoretical progress in adjacent fields, and to validate these systems experimentally in world-class facilities, closing the loop between theory and practice.
C&S aims to be a leading research group in the integration, development and testing of new theories on control, autonomous and cognitive systems (with and without human elements), while addressing industrial and societal needs. We tackle those problems in our domain that best fit our mission and objectives while at the same time are the most challenging from a scientific point of view. We set high standards for our team, our experimental facilities and the academic and industrial networks in which we cooperate.
Our Research Clusters
Aerospace Guidance, Navigation and Control focuses on the development of new generations of flight control systems, with superior performance and the ability to compensate automatically for technical faults. Topics include:
- Nonlinear dynamics, optimization and control
- Adaptive and reconfigurable flight control
- Helicopter flight dynamics and handling qualities
- State estimation and distributed control
- Vision-based autonomous operations
Aerospace Human-Machine Systems aims at supporting the human operator in manual and supervisory control tasks, through developing innovative human-machine interfaces and clever automation tools. Topics include:
- Cybernetic pilot perception and control models
- Haptic control systems, bio-dynamics
- Flight simulators and pilot training
- Ecological interfaces and cognitive systems
- Cockpit and air traffic control interfaces
Communication, Navigation & Surveillance in Air Traffic Management studies the sensors and systems enabling flight operations and Air Traffic Management (ATM), through simulating air traffic and designing novel equipment and algorithms. Topics include:
- Autonomous operations with Airborne Separation Assistance Systems
- Sense and avoid systems in the cockpit, on the ground and for UAVs
- Data-mining and big data applications, e.g., ADS-B
- Complexity of traffic patterns and traffic flows
- Scientific foundations of air traffic management and trajectory planning
The goal of the Micro Aerial Vehicle Lab is researching small flying systems. Micro Aerial Vehicles (MAVs) are aircraft’s with a span of not more than 1 m and a start weight of less than a kilogram.
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