  Including Model Predictive Control (MPC) in the undergraduate/graduate
control curriculum is becoming vitally important due to the growing adoption of
MPC in many industrial areas. In this paper, we present an overview of the
predictive control course taught by the authors at Imperial College London
between 2018 and 2021. We discuss how the course evolved from focusing solely
on the linear MPC formulation to covering nonlinear MPC and some of its
extensions. We also present a novel specification-based summative assessment
framework, written in MATLAB, that was developed to assess the knowledge and
understanding of the students in the course by tasking them with designing a
controller for a real-world problem. The MATLAB assessment framework was
designed to provide the students with the freedom to design and implement any
MPC controller they wanted. The submitted controllers were then assessed
against over 30 variations of the real-world problem to gauge student
understanding of design robustness and the MPC topics from the course.
