Flight Control Systems
With the ever increasing demand for greater degrees of agility and autonomy of aerospace vehicles, has led to major strides in flight control algorithms and system architectures.
There laboratory maintains strong multidisciplinary systems orientation that focuses on linear and nonlinear systems, dynamic optimization, feedback control, optimal path planning and decision-making in uncertain environments as well as computational and software aspects of flight systems.
The current graduate research in the lab is focused satellite attitude control as well as flight planning and flight control of dynamically unstable aircraft using H-infinity control methods on SO(3) and lie groups in general along with AI enabled real time trajectory generation for complex flight maneuvers involving post stall flight regimes.
For undergraduate students the lab supports and complements the theory courses in flight dynamics & controls, with actuated simulation platforms and experiments to emphasize implementation issues, as well as case studies of specific aerospace vehicles.
Autonomous Guidance and Navigation Systems
A surging interest in space launch operations and in Advanced Air Mobility (AAM) concepts is exacerbating the limitations of current practices, still heavily reliant on airspace segregation and not supporting the multimodal/intermodal evolution of air and space transport. For a successful integration of these new transport modes, it is critical that an acceptable level of safety is provided, requiring the development of novel digital tools (e.g., mission planning and decision support systems) that utilize advanced Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) technologies to allow a seamless integration of space operations in the current ATM network. The research work explores the role of Aerospace CPS (ACPS) and AI research to enable the safe, efficient and sustainable development of the air and space transport sector in the next decade. While the technical maturity of propulsive and vehicle technologies is relatively high, there are several opportunities and challenges associated with the adoption of CPS and AI to enable the integration of point-to-point suborbital spaceflight with conventional atmospheric air transport. Current research aims at developing robust and fault-tolerant CPS architectures that ensure trusted autonomous air/space transport operations with the given hardware constraints, despite the uncertainties in physical processes, the limited predictability of environmental conditions, the variability of mission requirements, and the possibility of both cyber and human errors.
CNS architectures for Urban Air Mobility
The long outstanding human inspiration to be able to traverse intra-city destinations aerially, avoiding traffic congestions is on the brink of materialization. Flight trials of Air Taxis paves the way for Urban Air Mobility (UAM). However, the greater challenge resides in formulating the Urban Air Traffic Management (UATM) structure and procedures to enable multiple aircraft to safely navigate their way in urban skies. The key technologies enabling UATM are Communications, Navigation and Surveillance (CNS) systems. This paper presents proposed configuration for CNS System to support UATM. Aircraft for UAM are supposed to operate within the aerial bounds of the cities away from conventional air traffic. Thus air traffic would be much dense and the Air Traffic Management (ATM) system required to control air mobility must provide integrity, robustness, security and high geo-spatial accuracy. Additionally, there is also a need for fast and accurate communication between traffic controller and the air vehicle. Communication requirements for UAM include Vehicle-to-Vehicle (V2V), Vertiport to vertiport and Vertiport to Vehicle communication. Navigation requires Self-positioning and Situational-awareness. Surveillance needs to be able to perform Ground stations detecting and tracking aircraft, position and Identification update. Research work in this area focuses on proposing viable CNS architectures for UAM and validating their performance.
Integration of UAS in National Air Space<
There is an increasing need to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) to perform missions of vital importance to national security and defense, emergency management, science, and to enable commercial applications. However, routine access by UAS to the NAS remains unrealized.
The UAS community needs routine access to the global airspace for all classes of UAS. Based on this need, the research aims to explore technologies to aid integration of UAS in NAS ensuring complete harmonization and interoperability between Piloted and Uninhibited aerial platforms, ensuring all the safety requirements of air traffic management.
Certification of AI/ML in safety critical avionics
Aviation safety certification is established upon verifying that all possible in flight occurrences have been perceived and verified. Whereas, in case of AI via machine-learning real-time software evolution cannot be perfectly predicted and verified in advance, this is the real challenge to certification. One solution is to specify machine learning functional boundaries in correlation with real-time monitoring and validation of machine learning solution. Implementation can be sequential with practical ground-based AI for scheduling and routing being the starting point. Next in line will be simpler, non-flight critical functions and finally moving on to flight or safety critical systems. The validation of certification requires that the final product operates in all modes and performs consistently and successfully under all actual operational and environmental conditions founded on conformance to the applicable specifications. In case of adaptive AI systems this can again be a difficult condition to prove. The research work in this area encompasses implementation of AI/ML techniques in a manner so as to be certifiable. Also amendments in certification processes to support usage of AI/ML in safety critical avionics is explored.
Human Factors in Aviation
Research work in this area covers wide range of issues that affect how people perform tasks in their work and non-work environments (especially those related to aviation safety, aircraft maintenance, flight, etc.). The study of human factors involves applying scientific knowledge about the human body and mind, to better understand human capabilities and limitations to achieve best possible fit between people and the system. Furthermore, this course aims to build social and personal skills (for example: communication and decision making) in order to improve safety and performance. Implementation of Human Machine Interactive Interface is an active domain of research.