Advanced Control Engineering

ME 7247
Northeastern University

Instructor: Laurent Lessard

This is a graduate-level course that covers topics in modern control engineering, including: optimal control, optimal filtering, robust/nonlinear control, and model predictive control. The main theme of the course is how uncertainty propagates through dynamical systems, and how it can be managed in the context of a control system. We will emphasize modern tools from computational linear algebra and convex optimization, and use Matlab for implementation. List of prerequisites:

  • Required: Basic linear algebra / differential equations; matrix/vector manipulations, subspaces, linear independence, solving ODEs and systems of linear equations. (e.g., MATH 2341)
  • Recommended: Basic linear systems theory; state-space equations, controllability/observability. (e.g. ME 5659 or EECE 7200).
  • Strongly recommended: Experience using Matlab. If you know how to use other scripting languages such as Python+Matplotlib, you’ll find Matlab very easy to learn and you should be fine.
No textbook or software purchase required; everything you need will be provided.

IMPORTANT: The notes below are from Fall 2021-22, which was the last time Prof. Lessard taught this course. These are scribed notes; they were written by students enrolled in the class and subsequently edited by Prof. Lessard. As the course evolves, the notes will continue to improve!


Course material About the class Resources