Research Portfolio
My research focuses on the control of negative imaginary (NI) systems, which naturally arise in many physical engineering systems.
I have established several theoretical results on the stability of NI systems under different control scenarios. More recently, I have been exploring how these ideas can be extended to modern control settings, where computation, learning, and digital implementation play a central role.
My work has demonstrated its utility across a range of engineering systems, including nanopositioning in atomic force microscopy, robotic control, and power systems.
Negative Imaginary Systems
A control framework for the stabilization of nonlinear NI systems.
Multi-Agent Nonlinear NI Systems
An output feedback consensus protocol for networked nonlinear NI systems.
Discrete-Time NI Systems
Digital control of negative imaginary systems under zero-order hold sampling.
More Research Coming Soon
Under Construction
I am currently documenting additional research projects, including work on Negative Imaginary Neural ODEs, State Feedback Equivalence to NI systems, Applciations in Nanopositioning of AFMs and Applications in Power Systems. Check back soon for updates.
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