At the control and optimization group, we engage in formulating, modeling, solving and implementing solutions to problems arising in the broad areas of control theory, dynamical systems and optimization. We always are hungry to learn and create newer mathematical techniques and state-of-the-art computational and technological applications cutting across multiple disciplines that not only include traditional grounds like mechanical/electrical engineering and computing but also in newer emerging platforms like systems biology, complex networks, learning and data science. We also make connections across disciplines to enrich understanding and transferring techniques from one area to another. Students get exposed on a regular basis to national and international level workshops, seminars and conferences where they get to network with people from a wide spectrum of backgrounds. The students get the freedom and guidance to walk along uncharted academic territories and have a healthy atmosphere that fosters productivity and holistic skill development.
Research Focus
The group has a holistic variety of activities that cater to a wide variety of tastes in students ranging from abstract mathematical analysis ( areas being recently explored include non-smooth analyis, differential geometry, game theory, koopman operators, event triggered control, distributed optimization) to hardcore computational cum experimental work (areas recently being explored include cloud computing, robotics, data driven science, machine learning).
Network systems
Network identification and reconstruction from data, network design and optimization for control, Information transfer in networks.
Multi-robot systems
Multi-robot systems with focus on rendezvous amidst constraints and digital design for robotics and other applications are among areas of interest to the group. Trajectory tracking, event-triggered and beam-forming in multi-agent robotic networks.
Optimization
Dynamic system approach to solving convex optimization problems. Online distributed optimization.
Control systems and decision sciences
Control systems and decision sciences (game theory and optimization) with applications in the analysis of engineering and economic systems.