Our lab lays considerable emphasis on control science and its associated areas of learning, optimization, newtork theory and system science. The lab has made contributions to different threads of theoretical research including, learning structure from measured data in networks with feedback, structured control, multiobjective control synthesis, and distributed computations over networked systems. Perspectives of research here, form the basis and guide our approach to many of the areas of applied research in our lab. The broad background enabled by this area has allowed the lab to be effective over a vast and diverse set of applied research areas.
Our lab has longstanding interest in nanoscience and nanotechnology. We have enabled new perspectives and methods for this area by leveraging control and systems science frameworks. Our experimental setup included customized atomic force microscopes, in-house realized optical tweezers for leveraging opto-mechanical affects and advanced TIRF based microscopy. These tools are themselves areas of research and are used as tools for other research. Our theoretical studies in this area include fundamental limits on energy needed for computation, fundamental sources of noise and relation of feedback to nanoscience and nanotechnology. Play the video below for details.
For the past decade, our lab has innovated technologies and methods for single molecule research. We have leveraged control and systems tools to realize new tools and perspectives. The research in nanoscience and nanotechnology also provides for a integrated environment for performing single molecule research with focus on intracellular transport and protein folding unfolding research. Theoretical, computational, learning and experimental topics are pursued. Play the video below for details.
Our Lab is developing a comprehensive approach that addresses the challenges to system reliability and power quality presented by widespread renewable power generation. By developing techniques for both centralized cloud-based and distributed peer-to-peer networks, the proposed system will enable coordinated response of many local units to adjust consumption and generation of energy, satisfy physical constraints, and provide ancillary services requested by a grid operator. The project will apply concepts from nonlinear and robust control theory to design self-organizing power systems that effectively respond to the grid events and variability. A key feature enabled by the proposed methodology is a flexible plug-and-play architecture wherein devices and small power networks can easily engage or disengage from other power networks or the grid. The project's design approach will be tested across many different scenarios while using more than 100 actual physical devices such as photovoltaics, battery storage inverters, and home appliances. Click here for more details.