Developing rigorous theory and implementation methods for complex high-order multiple time-scale nonlinear systems, focusing on hypersonic, planetary entry, Intelligence, Surveillance, Reconnaissance (ISR), multi-agent cooperative control of systems operating in outdoor GPS denied or reduced environments, and morphing unmanned air vehicles. Techniques used are Machine Learning; Nonlinear Singular Perturbation Theory; Robust and Fault Tolerant Adaptive Control, Online Real-Time System Identification; Formation Vehicle Control; Active Flow Control
Phase I IUCRC Texas A&M University: Center for Unmanned Air Systems
Tightly Integrated Navigation and Guidance for Multiple Autonomous Agents
Autonomous Navigation in Challenging Operational Environments: Demonstration
Unmanned Air System Departure Resistance Using Nonlinear Two-Time Scale Tracking Control
Autonomous Intelligent Detection Tracking and Recognition (AIDTR)
Enhancing the Cycle-of-Learning for Autonomous Systems to Facilitate Human-Agent Teaming
Agile Technology Development (ATD) – Air-Ground Coordinated Teaming
Machine Learning Control of Nonlinear, High Dimensional, Reconfigurable Systems
Real Time Adaptive Navigation and Control of Highly Nonlinear Autonomous Systems