This talk will discuss the technical challenges and theoretical foundations of controlling systems subject to constraints on their inputs and outputs, with a focus on their practical application to real-world problems. The talk will begin with an overview of invariant sets and model predictive control, which are two fundamental tools in constrained control. These tools will be demonstrated through their application to autonomous driving, advanced manufacturing, and cancer treatment. We will then discuss algorithms for real-time optimization and their application to battery cell balancing. Finally, we will discuss theoretical developments merging model predictive control with machine learning as well as applications to heating ventilation and air condition (HVAC) and automatic train stopping.
Claus Danielson, Ph.D
Wednesday, January 19, 2022 - 12:00 to 13:00
Pratt School of Engineering
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