7 papers
Adaptive Time-Domain Harmonic Control for Noise-Vibration-Harshness Reduction of Electric Drives
Klaus Herburger, Fabian Jakob, David Gänzle +2
Reducing Noise, Vibration, and Harshness (NVH) in electric drives is crucial for applications such as electric vehicle drivetrains and heat-pump compressors, where strict NVH requi…
Convergence and stability of Q-learning in Hierarchical Reinforcement Learning
Massimiliano Manenti, Andrea Iannelli
Hierarchical Reinforcement Learning promises, among other benefits, to efficiently capture and utilize the temporal structure of a decision-making problem and to enhance continual…
Hidden Convexity in Active Learning: A Convexified Online Input Design for ARX Systems
Nicolas Chatzikiriakos, Bowen Song, Philipp Rank +1
The goal of this work is to accelerate the identification of an unknown ARX system from trajectory data through online input design. Specifically, we present an active learning alg…
Complexity guarantees for risk-neutral generalized Nash equilibrium problems
Haochen Tao, Andrea Iannelli, Meggie Marschner +3
In this paper, we address \ac{SGNEP} seeking with risk-neutral agents. Our main contribution lies the development of a stochastic variance-reduced gradient (SVRG) technique, modifi…
Robustness of Online Identification-based Policy Iteration to Noisy Data
Bowen Song, Andrea Iannelli
This article investigates the core mechanisms of indirect data-driven control for unknown systems, focusing on the application of policy iteration (PI) within the context of the li…
Online Convex Optimization and Integral Quadratic Constraints: An automated approach to regret analysis
Fabian Jakob, Andrea Iannelli
We propose a novel approach for analyzing dynamic regret of first-order constrained online convex optimization algorithms for strongly convex and Lipschitz-smooth objectives. Cruci…