Seminars and Events at automatic control
All seminars are held at the Department of Automatic Control, in the seminar room M 3170-73 on the third floor in the M-building, unless stated otherwise.
Licentiate seminar by Alba Gurpegui Ramón : Minimax Regulator Problems for Positive Systems with their Application to Synchronization of Multi-Agent Systems
Disputation
From:
2025-02-28 10:15
to
12:00
Place: Lecture hall M:J, LTH
Contact: anders [dot] rantzer [at] control [dot] lth [dot] se
Alba Gurpegui Ramón is defending her Licentiate Thesis at the Department of Automatic Control, Lund
Date & Time: February 28th, 10:15-12:00
Location: Lecture hall M:J, LTH
Zoom:
Title: Minimax Regulator Problems for Positive Systems
with their Application to Synchronization of Multi-Agent Systems
Opponent: Professor Claudio Altafini, Linköpings universitet
Examiner: Associate Professor Richard Pates, Lunds universitet
Supervisor: Professor Anders Rantzer, Lunds universitet
Zoom: https://lu-se.zoom.us/j/5214958384?pwd=lu4Ur9XmR2ibHyXBBJ5FhgSDd4saVb.1&omn=66044979247
Meeting ID: 521 495 8384
Password: 06021997
Abstract: Exceptional are the instances where explicit solutions to optimal control problems are obtainable. Of particular interest are the explicit solutions derived for minimax problems, as they provide a framework for addressing challenges involving adversarial conditions and uncertainties. This thesis presents explicit solutions to a novel class of minimax optimal control problems for positive linear systems with linear costs, elementwise linear constraints in the control policy, and worst-case disturbances. Using dynamic programming theory, explicit solutions are derived for both finite and infinite horizons in discrete and continuous-time. Necessary and sufficient conditions for minimising the l1-induced gain of the system are derived and characterized by the disturbance penalty in the cost function of the minimax problem. A linear pogromming formulation of the minimax setting in the presence of nonnegative disturbances is also introduced, along with an analysis of the stability and detectability properties of the problem setting. Additionally, this thesis addresses the positive synchronization problem on undirected graphs, presenting a stabilizing feedback policy by solving the linear programming formulation of the introduced minimax optimal control problem class in the absence of disturbances. By leveraging explicit solutions to minimax optimal control and multi-agent synchronization problems, this work provides a computationally efficient and scalable framework for controlling large-scale systems.