activity
20202024
most citedPhysics-informed linear regression is competitive with two Machine Learning methods in residential building MPC

105 citations · 116 across the 8 of their papers we have counts for

collaborators

14 papers

math.OC2024★ 1 cited

Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation

Mathias Hudoba de Badyn, Jonas Binz, Andrea Iannelli +1

In this paper, a distributed dual-quaternion multiplicative extended Kalman filter for the estimation of poses and velocities of individual satellites in a fleet of spacecraft is a…

eess.SY2023★ 1 cited

MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches

Verena Häberle, Linbin Huang, Xiuqiang He +3

A fast and accurate grid impedance measurement of three-phase power systems is crucial for online assessment of power system stability and adaptive control of grid-connected conver…

eess.SY2023

Distributed Multi-Horizon Model Predictive Control for Network of Energy Hubs

Varsha Behrunani, Hanmin Cai, Philipp Heer +2

The increasing penetration of renewable energy resources has transformed the energy system from traditional hierarchical energy delivery paradigm to a distributed structure. Such d…

math.OC2023

A Dual System-Level Parameterization for Identification from Closed-Loop Data

Amber Srivastava, Mingzhou Yin, Andrea Iannelli +1

This work presents a dual system-level parameterization (D-SLP) method for closed-loop system identification. The recent system-level synthesis framework parameterizes all stabiliz…

eess.SY2023

Once upon a time step: A closed-loop approach to robust MPC design

Anilkumar Parsi, Marcell Bartos, Amber Srivastava +2

A novel perspective on the design of robust model predictive control (MPC) methods is presented, whereby closed-loop constraint satisfaction is ensured using recursive feasibility…

eess.SY2023

Error Bounds for Kernel-Based Linear System Identification with Unknown Hyperparameters

Mingzhou Yin, Roy S. Smith

The kernel-based method has been successfully applied in linear system identification using stable kernel designs. From a Gaussian process perspective, it automatically provides pr…