MEGR 3090: Introduction to Control Systems:
Control is an enabling technology in almost every modern electromechanical system. In fact, modern automobiles, aircraft, cell phones, and power plants all contain microcontrollers that use sensor data to make split-second decisions that conserve fuel, enhance operational efficiency, and even save lives. Students will gain an appreciation for the power of feedback control throughout this course, and will see the impact of automatic control in both simulation examples and a practical challenge project at the end of the course.
MEGR 7090/8090: Stability and Control of Nonlinear Systems:
This advanced graduate course focuses on mathematical techniques that are used to assess the stability of nonlinear systems and design controllers to stabilize unstable nonlinear systems and improve dynamic performance. Course topics include internal stability of equilibria, orbital stability, input-output stability, stability of interconnected systems, linearization-based control design, gain scheduling, and feedback linearization. Additionally, students are assigned to critically read and assess several journal publications that relate to the topics they are studying in class.
MEGR 3122: Dynamic Systems II:
Representing a continuation of Dynamics I, students will take their knowledge of dynamic modeling and use this knowledge to build control-oriented models of dynamic systems and conduct time- and frequency-domain analyses. The course covers the modeling of simple vibratory systems, RLC circuits, and electromechanical systems such as DC motors/generators. This course is intended as a prerequisite for MEGR-3090-002, which serves as a natural successor.
MEGR 3090: Flight Dynamics:
Tailored toward advanced undergraduate and first-year graduate students interested in aeronautics, this course covers the principles of steady, quasi-steady, and dynamic flight. The course covers the forces and moments acting on an aircraft, along with their aerodynamics, and covers longitudinal and lateral flight modes. Students partake in a small-scale design competition at the end of the course.
MEGR 7090/8090 – Advanced Optimal Control:
The field of optimal control focuses on the design of control systems that maximize or minimize a performance objective (for example, we may wish to minimize control energy expenditure or maximize energy generation of a renewable energy system), subject to constraints (e.g., actuator saturation limits, thermal limits, material strength limits, etc.). This course focuses on the development of mathematical tools for performing optimal control in both discrete-time and continuous-time contexts. Several optimal control techniques are introduced, including finite-dimensional local optimization techniques, dynamic programming, model predictive control, and Pontryagin’s minimum principle. Students are presented with the underlying theory in addition to several engineering examples for which the techniques can be applied.