From: 2024-05-24 10:30 to 11:30
Place: Seminar Room M 3170-73 at Dept. of Automatic Control, LTH
Contact: venkatraman [dot] renganathan [at] control [dot] lth [dot] se

Date & Time: May 24th, 10:30 - 11:30
Location: Seminar Room M 3170-73 at Dept. of Automatic Control, LTH 
Author: Anton Nyström
Title: Understanding Probabilistic Uncertainty Using Nu-Gap
Supervisor: Venkatraman Renganathan
Examiner: Anders Rantzer
Zoom link: https://lu-se.zoom.us/j/3246833728

Abstract:
When designing a controller to regulate a process, a major issue is the lack of complete knowledge of the process. A model is never perfect, and the discrepancy can have detrimental effects on control performance. Existing theory on the so called Nu-Gap metric provides a way to give the knowledge uncertainty a size and a chance to guarantee acceptable performance in regulating the process given that the uncertainty is not too large. However, it lacks nuance by only providing a binary answer for a given uncertainty size. This thesis extends the existing theory by adding more information, modelling the uncertainty using probability distributions and provides probabilistic guarantees as a result. The new theory provides a more nuanced answer, including a relationship between the guaranteed performance level and a probability of failure. The result is a fresh new perspective on probabilistic robust control and opens up for many new areas of research.