The Control Theory Seminar is at 3:30pm in Bechtel 240
Sep22  Rescheduled 
Sep29  Paulo Tabuada, University of California, Los Angeles 
Secure stateestimation and control for dynamical systems under adversarial attacks  
Control systems work silently in the background to support much of the critical infrastructure we have grown used to. Water distribution networks, sewer networks, gas and oil networks, and the power grid are just a few examples of critical infrastructure that rely on control systems for its normal operation. These systems are becoming increasingly networked both for distributed control and sensing, as well as for remote monitoring and reconfiguration. Unfortunately, once these systems become connected to the internet they become vulnerable to attacks that, although launched in the cyber domain, have for objective the manipulation of the physical domain. In this talk I will discuss the problem of stateestimation and control for linear dynamical systems when some of the sensor measurements are subject to an adversarial attack. I will show that a separation result holds so that controlling physical systems under active adversaries can be reduced to a stateestimation problem under active adversaries. I will characterize the maximal number of attacked sensors under which state estimation is possible and propose computationally feasible estimation algorithms. For this, I will use ideas from compressed sensing and error correction over the reals while exploiting the dynamical nature of the problem. Paulo Tabuada was born in Lisbon, Portugal, one year after the Carnation Revolution. He received his "Licenciatura" degree in Aerospace Engineering from Instituto Superior Tecnico, Lisbon, Portugal in 1998 and his Ph.D. degree in Electrical and Computer Engineering in 2002 from the Institute for Systems and Robotics, a private research institute associated with Instituto Superior Tecnico. Between January 2002 and July 2003 he was a postdoctoral researcher at the University of Pennsylvania. After spending three years at the University of Notre Dame, as an Assistant Professor, he joined the Electrical Engineering Department at the University of California, Los Angeles, where he established and directs the CyberPhysical Systems Laboratory. Paulo Tabuada's contributions to cyberphysical systems have been recognized by multiple awards including the NSF CAREER award in 2005, the Donald P. Eckman award in 2009 and the George S. Axelby award in 2011. In 2009 he cochaired the International Conference Hybrid Systems: Computation and Control (HSCC'09) and in 2012 he was program cochair for the 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys'12). He also served on the editorial board of the IEEE Embedded Systems Letters and the IEEE Transactions on Automatic Control. His latest book, on verification and control of hybrid systems, was published by Springer in 2009. 

Oct6  Javad Lavaei, Columbia 
GraphTheoretic Algorithm for Arbitrary Polynomial Optimization Problems with Applications to Distributed Control, Power Systems, and Matrix Completion  
Optimization theory plays a crucial role in the design, analysis, control, and operation of realworld systems. The development of efficient optimization techniques and numerical algorithms for nonlinear optimization problems has been an active area of research for many years. The goal is to design an efficient, robust and scalable method for finding a global or nearglobal solution. This still remains as an open problem for the general class of polynomial optimization, including combinatorial optimization. In this talk, we study a general polynomial optimization using a semidefinite programming (SDP) relaxation. The existence of a rank1 matrix solution to the SDP relaxation enables the recovery of a global solution of the original problem. We propose a graphtheoretic technique to sparsify the optimization problem of interest such that its SDP relaxation will have a guaranteed lowrank solution. As a byproduct, we show that every arbitrary polynomial optimization admits a sparse quadratic representation whose SDP relaxation has a matrix solution with rank at most 3. This result provides a basis for finding a nearglobal solution by approximating the rank3 SDP solution with a rank1 matrix. In this talk, we apply our technique to three longstanding problems: optimal distributed control, power optimization problem, and lowrank matrix completion. We also offer more than 100K simulations for control and optimization over realworld power systems (such as Polish and New England systems). We verify that our algorithm usually finds solutions with global optimality degrees close to 99.9%. Since generalpurpose SDP solvers can hardly accommodate sparse SDP problems with millions of parameters, we also propose a distributed algorithm whose iterations consist of only simple multiplication and eigenvalue decomposition over smallsized matrices. 

Oct13  Lalitha Sankar, Arizona State University 
Consequences of Cyberattacks on the Electric Power System  
The electric power system is a complex network that is monitored and controlled by a distributed network of humanmachine interfaced control systems. These cyber systems are just as vulnerable to sophisticated cyberattacks as are traditional networked information systems; however, the consequences of such attacks can be much severe for such critical infrastructure. Recent results on cyberattacks on the electric grid have demonstrated the design of unobservable attacks within the context of specific (cyber) processing units, notably state estimators. However, very little is known of the consequences of sophisticated and welldesigned cyberattacks on the electric power system as a whole. Furthermore, a related open question is that of whether such attacks can be detected when the endtoend cyber control system is taken into account. In this talk, we highlight our recent results towards addressing these questions including: (i) development of a timeprogression model for cyberfunctionalities in the electric power system that is essential for sophisticated and realistic attack and countermeasure design and testing; (ii) design of sophisticated unobservable attacks on state estimation with only local knowledge of the network topology; (iii) consequences of such unobservable attacks on realtime dispatch and control operations; and (iv) effect of such attacks on distributed EMSs. Joint work with Jingwen Liang, Jiazi Zhang, Oliver Kosut, and Kory Hedman 

Oct20  Pablo Parrilo, MIT 
Partial facial reduction: simplified, equivalent SDPs via approximations of the PSD cone  
Many convex optimization problems arising in practice (particularly instances automatically generated by parsers) are not strictly feasible, i.e., the feasible set does not have an interior point. To this end, we develop a practical semidefinite programming (SDP) facial reduction procedure that utilizes computationally efficient approximations of the positive semidefinite cone. The proposed method simplifies SDPs with no strictly feasible solution (a frequent output of parsers like YALMIP or SOSTOOLS) by solving a sequence of easier optimization problems, and serves as a useful preprocessing technique for general SDP solvers. We demonstrate effectiveness of the method on SDPs from the literature, and describe our publiclyavailable software implementation. Joint work with Frank Permenter (MIT). Preprint available at arXiv:1408.4685. 

Oct27  Sayan Mitra, University of Illinois at UrbanaChampaign 
From Simulations to Proofs  
Combining simulations with formal analysis can improve the design, verification, and validation processes for embedded and cyberphysical systems. In this talk, I will present an overview of the algorithms we have developed to derive boundedtime formal guarantees from numerical simulations and static analysis of models. These algorithms are targeted for hybrid models of distributed and cyberphysical systems and they require either implicit or explicit annotations. They are always sound and also complete for robust safety and temporal precedence properties. For large networked models, the annotations can be derived compositionally. I will mention the lessons learned and the outstanding challenges in applying them to verify a parallel landing protocol and a cardiac cellpacemaker network. Sayan an Associate Professor of Electrical and Computer Engineering at the University of Illinois at UrbanaChampaign. His research is onalgorithmic and software tools for design and analysis of distributed, embedded and cyberphysical systems. Sayan graduated from MIT in 2007 and spent one year as a postdoctoral researcher at CalTech. His received several Best paper awards, National Science Foundation's CAREER award, AFOSR Young Investigator Research Program Award, IEEE HKN Best paper award and IEEEHKN C. Holmes MacDonald Outstanding Teaching Award. 

Nov3  Ramesh Johari, Stanford 
Nov10  Steven Low, Caltech 
Design and Stability of Loadside Frequency Control  
Frequency control maintains the frequency of a power system tightly around its nominal value when demand or supply fluctuates. It is traditionally implemented on the generation side though loadside participation can offer advantages in fuel, emission, and responsiveness. We present a systematic method to design ubiquitous continuous fastacting distributed load control for frequency regulation in power networks, by formulating an optimal load control (OLC) problem where the objective is to minimize the aggregate cost of tracking an operating point subject to power balance over the network. We prove that the swing dynamics and the branch power flows, coupled with frequencybased load control, serve as a distributed primaldual algorithm to solve OLC. We show that loadside primary frequency control that rebalance power and resynchronize frequency can be implemented in a completely decentralized manner because the local frequency deviations at each bus convey exactly the right information about the global power imbalance for the loads to make individual decisions that turn out to be globally optimal. Loadside secondary frequency control that restores the nominal frequency can be implemented in a distributed manner using message passing among neighbors. Simulations show that the proposed algorithms also improve the transient performance. (Joint work with Changhong Zhao, Enrique Mallada (Caltech), Ufuk Topcu (UPenn), Lina Li (Harvard)) 

Nov17  Kevin Murphy, Google 
Nov24  Marija Ilic, Carnegie Mellon University 
Control Theory Seminar Series, Spring 2014 
Control Theory Seminar Series, Fall 2013 