Teaching
ECEN 1500 - Sustainable Energy
Explores how energy is generated and used in today's society. Through collaborative discussion and hands-on data collection, students will analyze the engineering challenges, fundamental limits, and potential solutions to meeting our energy needs sustainably. Students will learn to analyze numerical data, estimate orders of magnitude, and apply mathematical methods in their own lives and in the ongoing energy debate.
ECEN 3300 - Linear Systems
Characterization of linear time-invariant systems in time and frequency domains. Continuous time systems are analyzed using differential equations and Laplace and Fourier transforms. Discrete time systems are analyzed using difference equations, Z-transforms and discrete time Fourier transforms. Sampling and reconstruction of signals using the sampling theorem. Applications of linear systems include communications, signal processing, and control systems.
ECEN 4138/5138 - Control Systems Analysis (Fall 2017)
Modeling of dynamic systems using block diagrams. The importance of feedback; analysis and design of feedback control systems using root locus, Bode, and Nyquist methods. Introduction to the concept of state and state variable techniques.
ECEN 5418 - Automatic Control Systems
Coverage of principles of control systems with Multiple Inputs and Multiple Outputs (MIMO). Topics include Mimo state-space theory, applications of the singular value decomposition (SVD), coprime factorization methods, frequency domain topics, and an introduction to H-infinity design.
ECEN 5448 - Advanced Linear Systems
Offers a state space approach to analysis and synthesis of linear systems, state transition matrix, controllability and observability, system transformation, minimal realization, and analysis and synthesis of multi-input and multi-output systems.
ECEN 5458 - Sampled-Data and Digital Control Systems (Spring 2018)
Since digital microprocessors are inexpensive and easy to program, most (continuous-time) systems (such as those shown) are digitally controlled in practice. Take this course to learn: how to analyze sampled-data systems (mixed discrete-time and continuous-time systems), and how to design digital controllers and analyze their performance using both frequency-domain (root locus, Bode, Nyquist) and time-domain (state-space) methods.