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20232025
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7 papers · 1 filter

math.OC2024

A Cone-preserving Solution to a Nonsymmetric Riccati Equation

Emil Vladu, Anders Rantzer

In this paper, we provide the following simple equivalent condition for a nonsymmetric Algebraic Riccati Equation to admit a stabilizing cone-preserving solution: an associated coe…

eess.SY2024

On PI-control in Capacity-Limited Networks

Felix Agner, Anders Rantzer

This paper concerns control of a class of systems where multiple dynamically stable agents share a nonlinear and bounded control-interconnection. The agents are subject to a distur…

math.OC2024

Duality-based Dynamical Optimal Transport of Discrete Time Systems

Dongjun Wu, Anders Rantzer

We study dynamical optimal transport of discrete time systems (dDOT) with Lagrangian cost. The problem is approached by combining optimal control and Kantorovich duality theory. Ba…

eess.SY2024

Hydraulic Parameter Estimation for District Heating Based on Laboratory Experiments

Felix Agner, Christian Møller Jensen, Anders Rantzer +2

In this paper we consider calibration of hydraulic models for district heating systems based on operational data. We extend previous theoretical work on the topic to handle real-wo…

eess.SY2024

A data-based comparison of methods for reducing the peak volume flow rate in a district heating system

Felix Agner, Ulrich Trabert, Anders Rantzer +1

This work concerns reduction of the peak flow rate of a district heating grid, a key system property which is bounded by pipe dimensions and pumping capacity. The peak flow rate co…

math.OC2024

Optimal Mass Transport of Nonlinear Systems under Input and Density Constraints

Dongjun Wu, Anders Rantzer

We investigate optimal mass transport problem of affine-nonlinear dynamical systems with input and density constraints. Three algorithms are proposed to tackle this problem, includ…

eess.SY2024

Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification

Bruce D. Lee, Anders Rantzer, Nikolai Matni

The strategy of pre-training a large model on a diverse dataset, then fine-tuning for a particular application has yielded impressive results in computer vision, natural language p…