Control and Decision Systems
Research focused on developing techniques to create intelligent, autonomous, and networked dynamic systems that can operate predictably, efficiently, and reliably in complex environments. The primary theoretical areas of research include distributed and robust control, distributed optimization, robust and risk-adjusted optimization, system identification, game theory, nonlinear and adaptive control, and machine learning based control. The applications of interest include health care, mobile autonomous robots, security, multi-agent systems, cyber-physical systems, hydraulic systems, magnetic resonance systems, and power systems.
Primary Faculty
Affiliate Faculty
