Un of Tenn | Math Department

Seminars and Colloquiums
for 2010-2011

Week of April 25, 2011

Speaker:

Mr. Jacob Ogle, Monday
Dr. S. Sathananthan, Tennessee State University, Monday
Dr. Andreas Malikopoulos, NTRC and Weinberg Fellow at ORNL, Wednesday
Mr. Zachary Smith, Wednesday

If you are interested in giving or arranging a talk for one of our seminars or colloquiums,
please review our calendar.

If you have questions, or a date you would like to confirm, please contact Dr. Fernando Schwartz.

Monday, April 25

TOPOLOGY SEMINAR
TIME: 12:20 p.m. – 1:10 p.m.
ROOM: Ayres Hall 406
SPEAKER: Mr. Jacob Ogle
TITLE: The Zariski Topology and Irreducibility
ABSTRACT: I will give a brief introduction to the Zariski topology, the usual topology studied in algebraic geometry. This topology is coarser than the usual topology on the real numbers, but it also allows one to define a topology on any field. We will discuss some of the relationships between the algebraic properties and the topological properties. Then we will turn our attention to irreducibility, and I will summarize some of my recent results in this area.

SIAM Student Chapter and Math Biology Seminar
TIME: 3:35 p.m.
ROOM: Ayres Hall 405
SPEAKER: S. Sathananthan, Tennessee State University
TITLE: STOCHASTIC DISCRETE-TIME SYSTEMS: STABILITY AND CONTROL
ABSTRACT: Stability and stabilization of both linear and nonlinear discrete-time stochastic systems under Markovian switching is considered. Feedback stabilization and optimal cost criterion are investigated. Our objective is to show how linear feedback laws can be formulated to stabilize the nonlinear system and, at the same time maximize the bounds on this nonlinear perturbing function which the system can tolerate without becoming unstable. Robustness of the results are also investigated. We provide motivation for the research and demonstrate our results with examples.

Pizza will served before the talk at 3:15.

Wednesday, April 27

ANALYSIS SEMINAR
TIME: 3:35 p.m
ROOM: Ayres Hall 114
SPEAKER: Mr. Zachary Smith
TITLE: Weakly Factored Spaces and their duals, part 3

COLLOQUIUM
TIME: 3:35 p.m
ROOM: Ayres Hall 111
SPEAKER: Andreas Malikopoulos, NTRC and Weinberg Fellow at ORNL
TITLE: Self-Learning Identification and Stochastic Control for Autonomous Intelligent Propulsion Systems
ABSTRACT: Increasing demand for improving fuel economy and reducing emissions has stimulated significant research on and investment in advanced propulsion systems. These systems have introduced a number of controllable variables that have enhanced our ability to optimize engine operation. In particular, the determination of the optimal values of these variables, referred to as engine calibration, has been Shown to be especially critical for achieving high engine performance and fuel economy while meeting emission standards. State-of-the-art engine calibration methods generate a static tabular relationship between the controllable variables and steady-state operating points or specific driving conditions, e.g., vehicle speed profiles for highway and city driving. These methods, however, seldom guarantee optimal engine operation for common driving habits, e.g., stop-and-go driving, rapid acceleration, or rapid braking. Each individual driving style is different and rarely meets those driving conditions of testing for which the engine has been optimized.

This talk presents the theory and algorithms for making the engine of a vehicle into an autonomous intelligent system capable of learning its optimal operation in real time while the driver is driving the vehicle. The engine is treated as a controlled stochastic system, engine operation is modeled as a controlled Markov chain and engine calibration is formulated as a sequential decision-making problem under uncertainty. The engine's ability to learn its optimum operation is not limited to a particular driving style. The engine can learn to operate optimally for different drivers, when the drivers indicate their identities through their car keys before starting the vehicle.

The ultimate goal of this approach is to fully exploit the existing propulsion technologies in terms of the optimum specified performance criteria, e.g., fuel economy, or pollutant emissions, that can be achieved. It aims to provide an answer to the following question: "For a propulsion system with a given technology, what is the maximum efficiency that a driver can get with respect to his/her driving habits?" The long-term potential benefits of this approach are substantial. True fuel economy of vehicles will be increased while meeting emission standard regulations; drivers will be able to evaluate their driving behavior and learn how to improve fuel economy and reduce emissions by modifying it. This capability can also be especially appealing in advanced hybrid-electric propulsion systems when real-time optimization of the power management is considered.

Refreshments will be available in Room 401 at 3:15 p.m.

Past notices: