Network Systems Applications
Wednesday, October 4
Session II: 1:50 – 3:10
Engineering 2, 5TH Floor, Room 599
Ricardo Sanfelice, UCSC (Chair)
Ricardo Sanfelice is Associate Professor of Computer Engineering at UCSC. He received his M.S. and Ph.D. degrees from UCSB and was a postdoc at MIT. His research interests are in modeling, stability, robust control, observer design, and simulation of nonlinear and hybrid systems with applications to power systems, aerospace, and biology.
Marcella Gomez, UCSC
Marcella joined the faculty this fall at UC Santa Cruz in the department of Applied Mathematics and Statistics as assistant professor. She received her PhD from Caltech in 2015 and a B.S. from UC Berkeley in 2009; both degrees in mechanical engineering. Her research interests are in synthetic and systems biology.
Research in synthetic biology finds itself in a pivotal time. Synthetically built networks are no longer novelties but have real implications for impactful applications in our society. This talk presents current work and challenges in the design of genetic networks. We look to a control and dynamical systems approach to understanding the underlying robustness in natural networks for our own design purposes.
Yu Zhang, UCSC
Yu Zhang is an Assistant Professor in the UCSC Department of Electrical Engineering. Prior to joining UCSC, he was a postdoc at UC Berkeley and Lawrence Berkeley National Laboratory. His research interests span the broad areas of smart power grids, big data analytics, optimization and learning.
This talk deals with the non-convex power flow and power system state estimation problems, which play a central role in dynamic monitoring and operation of electric power networks. The objective of the power flow problem is to obtain the state of the system from a set of noiseless measurements, whereas the state estimation problem deals with noisy measurements. The semidefinite programming (SDP) and second-order cone programming (SOCP) relaxations are then leveraged to cope with the inherent non-convexity of the power flow problem. It is shown that both conic relaxations recover the true PF solution under mild conditions. By capitalizing on this result, a penalized convex problem is designed for the state estimation. This penalized SDP problem is obtained from the aforementioned SDP relaxation, by adding a weighted least absolute value penalty for fitting noisy measurements. Strong theoretical results are derived to quantify the optimal solution of the penalized SDP, which is shown to possess a dominant rank-one component formed by lifting the true voltage vector. Numerical results on benchmark systems will be demonstrated to corroborate the merits of the proposed convexification framework.
Abhishek Halder, UCSC
Abhishek is an Assistant Professor in the UCSC Department of Applied Mathematics & Statistics. Before that he held postdoctoral positions in the Department of Mechanical and Aerospace Engineering at University of California, Irvine, and in the Department of Electrical and Computer Engineering at Texas A&M University. His research interests are in stochastic systems, control and optimization with application focus on large scale cyberphysical systems such as the smart grid and unmanned aerial traffic management.
There is a pressing demand for designing a dedicated traffic management system for unmanned aerial vehicles, commonly termed as drones, operating at low altitude. Unlike the existing manned air traffic management, the unmanned air traffic management (UTM) system is envisioned to be highly autonomous, and must be provably safe while guaranteeing high throughput. As a networked cyber-physical system, UTM has many unique design challenges which essentially stem from the fact that different groups of drones may have conflicting business needs, and yet are required to share the same physical space-time resource. This talk will elucidate these challenges and then propose a UTM architecture with a suite of protocols that can be thought of as the “rules of the sky”. Time permitting, the talk will go into algorithmic details associated with one of the protocol, and make a case that they lead to interesting systems-control research problems.