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Texas A&M University College of Engineering

Autonomous, Nonlinear Control of Air, Space and Ground Systems

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


Novel Multiple Time Scale Adaptive Control for Uncertain Nonlinear Dynamical Systems

Interferometric Vision and Optomechanical Accelerometer Sensing for Navigation, Guidance, and Adaptive Control of Hypersonic Vehicle Platforms

Tightly Integrated Navigation and Guidance for Multiple Autonomous Agents

State Constrained Adaptive Flight Control, Phase I

Robust Threat Detection for Ground Combat Vehicles with Multi-Domain Surveillance in Hostile Environments

Phase I IUCRC Texas A&M University: Center for Unmanned Air Systems

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) 

State Constrained Adaptive Flight Control, Phase II

Enhancing the Cycle-of-Learning for Autonomous Systems to Facilitate Human-Agent Teaming

Agile Technology Development (ATD)  – Air-Ground Coordinated Teaming

Unmanned Vehicle Autonomous Algorithms

Machine Learning Control of Nonlinear, High Dimensional, Reconfigurable Systems

Machine Learning Control of Morphing Micro Air Vehicles

Real Time Adaptive Navigation and Control of Highly Nonlinear Autonomous Systems

Autonomous Intelligent Agents and Displays for Automation and Real-Time Simulation of Non-Controlled Airports

 

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