**Teaching and Courses**

**Michael Lemmon,
University of Notre Dame**

**
Introduction to Electrical Engineering - EE20224:
**This lab manual was based on a book
originally written by Paul H. Dietz (

** Power System Analysis - EE 30372**

The objective of this course is to provide
students with an overview of interconnected 3-phase power system operation.
The student will learn how to model the basic components of such
systems;
transmission lines, transformers, generators, and loads. The
student
will learn about power flow analysis and its role in economic
dispatch and generation control. Additional topics include transient
stability and short circuit protection.

**Power Electronics - EE40442**

This course studies the use of electronics in the conversion of electrical power. The topics covered in this course include modeling, analysis, and control techniques for power electronics; the design of power circuits including inverters, rectifiers, and DC-DC converters; feedback control principles, and characteristics of real components. Students will assist in the design and construction of an autonomous PV power system.

**Advanced Control Systems - EE 60655**
This is graduate level course introducing advanced concepts
in the feedback control of linear and nonlinear dynamical processes to students that
may not necessarily specialize in control. So one might think of this as a "grand tour"
of the major accomplishments in control theory.
Prerequisites for this course are graduate level course work in linear systems theory and random processes.

**Robust Control ā
EE60555**
This course studies the design of robust optimal controllers for linear
continuous-time systems. Topics include: normed linear signal/system
spaces, matrix fraction descriptions, uncertain systems, robust
stability and performance, loopshaping, and the use of linear
fractional transformations in solving the generalized regulator
problem.

This course is a rigorous introduction to the classical theory of optimal control. The topics covered in this course include optimization of static functions, the calculus of variations, Pontragin's principle, dynamic programming, linear quadratic optimal control, non-cooperative differential games with applications to control theory, and price-based control of decentralized dynamical systems.

**Nonlinear
Control - EE60580**
This course studies the analysis and design of nonlinear feedback
control systems using Lyapunov and passivity methods. Topics include:
classical Lyapunov stability theory, input-to-state stability,
uniform ultimate boundedness, passivity methods, feedback designs for
stabilization and disturbance rejection, exact feedback
linearization, nonlinear H-infinity control, sliding mode control

**Linear Systems Theory
- EE60550**
State variable descriptions of linear dynamical systems. Solution of
state equations for continuous-time and discrete-time
systems. Input-output descriptions: impulse response and transfer
function. Controllability, observability, canonical forms,
stability. Realizations of input-output descriptions. State feedback
and state observers. Polynomial matrix and matrix fraction
descriptions of linear, time-invariant systems.

**
Applied State Estimation - EE67033
**
This course covers techniques used in estimating the state of a dynamical system. The course reviews basic concepts in linear systems, Bayesian estimation, and minimum mean-square estimation followed by the introduction of the conventional Kalman filter in both discrete-time and continuous-time formats. The course examines extensions of the Kalman filter that include the extended and unscented Kalman filter as well as the H-infinity filter. The course may also cover some advanced topics in Multi-target tracking, state estimation over networks, and the use of Markov Chain Monte Carlo (MCMC) methods.

**
Special Studies- Forecasting Regime-Shifts in Complex Dynamical Processes- EE67598
**
Regime shifts occur when a dynamical system's state shifts irreversibly from the neighborhood of a