NASA SBIR 2018-II Solicitation

Proposal Summary

 18-2- A2.02-3903
 Unmanned Aircraft Systems (UAS) Technologies
 Evolving and Certifiable Autopilot for Unmanned Aerial Systems
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Design Analysis & Research Corporation
910 East 29th
Lawrence, KS 66046
(785) 832-0434

PRINCIPAL INVESTIGATOR (Name, E-mail, Mail Address, City/State/Zip, Phone)
Willem Anemaat
910 E. 29th Street
Lawrence, KS 66046 - 4920
(785) 832-0434

BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Willem Anemaat
910 E. 29th Street
Lawrence, KS 66046 - 4920
(785) 832-0434

Estimated Technology Readiness Level (TRL) :
Begin: 5
End: 7
Technical Abstract (Limit 2000 characters, approximately 200 words)

An intelligent flight control system is developed with learning capabilities and a high degree of assurance that can be certified by the FAA and tested on a modular reconfigurable UAS.  Existing lack of intelligence, adaptability and high performance of current automatic flight controllers is addressed by taking advantage of high-performance computing platforms, state-of-the-art machine learning and verification algorithms to develop a new intelligent, adaptable and certifiable flight control system with learning capabilities.

The autopilot system will be able to learn from flight experience and develop intuition to adapt to a high level of uncertainties. To provide a high degree of assurance and make the learning autopilot system safe and certifiable, a conventional autopilot system is integrated based on a run-time assurance architecture. A monitor is developed to check aircraft states and envelope protection limits and handover aircraft control to a conventional autopilot system if needed. Provable guarantees of the monitor and the controllers is provided using formal analysis. The hybrid flight control system has adaptability and intelligence of skilled pilots and is capable of performing complex analysis and decision making in real-time. An artificial neural network model is built and trained to mimic the performance of classical robust optimal controllers, extending robustness, adaptability and curiosity of artificial neural network controllers and integrating a Real-Time Assurance system.

Technology demonstration of the intelligent flight control system is achieved by flight testing of a Modular Air Vehicle, where the configuration can be customized to fit flight test needs and test adaptability of the proposed technology.  A Modular Air Vehicle is designed and prototyped.  Once the intelligent flight controllers are integrated with the airframe, ground and flight tests will be carried out to verify the performance and reliability of the proposed technology.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

The developed autopilot could be used on many of NASA UASs and newly developed aircraft, such as the X-57 and the GL-10 Greased Lightning.  The Modular Air Vehicle can be used for all sorts of research projects since it is very easy to change the configuration for any of NASA needs for flight test research, VTOL research, autopilot research, system failure research, etc.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

The autopilot can be used on any commercially and military available UAS system.  The Modular Air Vehicle will be commercialized for use at universities and other research institutes world-wide for flying research on different type of unmanned vehicles.  A smaller version will be developed for science and technology classes in high schools.

Duration: 24

Form Generated on 05/13/2019 13:31:23