Research Projects

Optimal Control of Switched Systems for MCM

Online (i.e., real-time) adaptive optimal controllers for maritime systems that operate in complex environments where intermittent sensing and actuation render modern online optimal control methods unsuitable.

ONR N00014-21-1-2481 (ongoing)

Details and publications

Operator Theory for Identification and Verification

We seek the development of new operator theoretic kernel methods that can harness data obtained from black and gray box dynamical systems.

NSF 2027999 (ongoing)

Details and publications

Neuromuscular retraining to relieve joint contact forces

Alteration of gait to minimize joint contact forces, thereby delaying the onset and slow down the progression of knee osteoarthritis.

Unfunded (ongoing)

Details and publications

Mine Countermeasures and Optimal Control

This project developed computational methods for reinforcement learning in continuous-time dynamic systems.

ONR N00014-16-1-2091 (completed)

Details and publications

Development of Reduced-order System Models for Next Generation Comfort Cooling Equipment

This project will focus on reduced-order modeling of HVAC units using both experimental research and first-principle model-based analysis.

OCAST AR41-042 (completed)

Details and publications

Wind-Aware UAV Navigation

Development of theoretical and computational tools that enable prediction and exploitation of low-altitude gust information for autonomous aircraft operations.

NSF 1925147 (completed)

Details and publications

Scale Separation for Wind-aware Guidance and Control

In this project we developed a hierarchical control architecture that exploited the spatiotemporal scale separation in the atmospheric boundary layer wind flow dynamics.

NASA - EPSCoR - RIG 2019-33 (completed)

Details and publications

An output feedback approach to adaptive optimal control of unmanned multi-agent teams

The objective of this project is to develop novel solutions to the multi-agent optimal decision making problem by formulating it as an output-feedback adaptive optimal control problem.

AFRL FA8651-23-1-0006 (completed)

Details and publications

Model-Aware Reinforcement Learning

Methods for online real-time learning that are robust to modeling errors and abrupt changes in the dynamic models using a model-aware reinforcement learning framework.

AFRL FA8651-19-2-0009 (completed)

Details and publications

Operator Theory for Control Synthesis

We are developing novel operator theoretic techniques for data and model-driven synthesis of control via control Lyapunov functions and solution of optimal control problems.

AFOSR FA9550-20-1-0127 (completed)

Details and publications

SCC Home