Autonomous Intelligent Health Monitoring for Robust Fault-Tolerant Control of Multi-Modal System

The overall goal of this project is to develop a robust autonomous intelligent real-time system for Uninhabited Aerial Combat Vehicles (UCAV) to achieve the desired flight performance by integrating effective Health Monitoring and Failure Detection and Identification (HM-FDI) with optimal control strategies to accommodate unanticipated failures and multiple modes of operation. SSCI has already done ground-breaking research in this area, which will be fully leveraged to further advance the state-of-the-art in Intelligent Autonomy. In order to achieve these objectives, we plan to carry out the following tasks in collaboration with Professor Karl Hedrick of the University of California, Berkeley: (i) Formulate the HM-FDIR problem in multiple operating regimes for UCAVs; (ii) Derive algorithms for real-time calculation of Achievable Dynamic Performance (ADP) and reachable sets; (iii) Implement an efficient robust HM-FDIR system for the X-45A as a test vehicle; (iv) Implement higher decision-making levels including the trajectory generation, path planning and mission planning levels; and (v) Evaluate the performance of the proposed autonomous intelligent flight control and management system using a X-45A (Boeing-Darpa UCAV) simulation. NASA Ames Rotorcraft Research Center (Dr. Mark Tischler) will provide technical evaluation and flight demonstration support during Phase II of the project.