899 citations · 4k across the 136 of their papers we have counts for
166 papers
Stability Analysis in IBR-Dominated Grids: Model-Based and Data-Driven Methodologies
Federico Cecati, Yang Wu, Florian Dörfler +3
Stability issues in converter-dominated grids have a multifold nature, where static, small-signal and large-signal phenomena can influence each other. Capturing the interplay among…
Identification of -Asymmetric Impedances as Complex Transfer Functions Using a Single Arbitrary Excitation
Mohamed Abdalmoaty, Zheran Zeng, Dongsheng Yang +1
Cross-coupling between the coordinates makes the identification of asymmetric grid impedances a challenging problem, particularly near the fundamental frequency where the asym…
Bounded Linear Programs for Data-Driven Optimal Control via Moment-Matching
Andrea Martinelli, Lucia Pezzetti, Niklas Schmid +2
Linear programming (LP) formulations offer a conceptually elegant approach to infinite-horizon, model-free nonlinear optimal control in continuous spaces. However, in addition to t…
GENCO - A Unified Neural Solver Embedded in a Development Framework for Steady-State Grid Analysis
Alban Puech, Matteo Mazzonelli, Tamara R. Govindasamy +19
Foundation models are transforming business workflows and boosting productivity, yet they remain largely absent from engineering domains such as power system analysis, where strict…
Coordinated Primary Frequency Regulation and Grid-Forming Control for Wind Turbine Generators
Meng Chen, Yufei Xi, Lin Cheng +2
Conventional grid-forming (GFM) control strategies often treat the DC source as an unconstrained link, creating mismatches when applied to the wind turbine generators (WTGs). Focus…
Foundations of Reinforcement Learning and Control:Connections and New Perspectives
Claire Vernade, Onno Eberhard, Martha White +4
Reinforcement learning and control theory are two adjacent scientific fields that focus on optimizing the controller of unknown dynamical systems using feedback. While both fields…
Chess on Ice: Curling Tactical Decision-Making via Backward Induction and Deep Reinforcement Learning
Patrick Oberlin, Matteo Cederle, Aren Karapetyan +3
Curling is often referred to as "Chess on Ice", owing to the tactical complexity of its decision-making process. Yet unlike chess, curling remains largely underexplored from a mach…
Fundamental Limitations of Data-Driven Control: A Statistical Decision Perspective
Jiabao He, Feiran Zhao, Yushan Li +3
Substantial research efforts have been devoted to the design of data-driven controllers; however, comparatively less is known about their statistical performance and fundamental li…
Gaussian behaviors and stochastic data-driven control
András Sasfi, Alberto Padoan, Ivan Markovsky +1
We propose a stochastic behavioral modeling framework, termed Gaussian behaviors, which augments a deterministic linear time-invariant (LTI) behavior with a Gaussian noise componen…
Geometric Decentralized Stability Certificate of Power Electronics-Dominated Power Systems Covering Variable Operating Points
Ruohan Leng, Linbin Huang, Liangxiao Luo +3
The integration of power converters is profoundly changing the power system dynamics and poses significant challenges for stability analysis. The dynamic interactions between the p…
Adaptive Linear Quadratic Control of Unknown Linear Time-Varying Systems via Policy Gradient Methods
Feiran Zhao, Florian Dörfler
Unknown linear time-varying (LTV) systems require the control policy to adapt from online closed-loop data as dynamics evolve. Existing methods usually update the policy by solving…
A Data-Enabled Primal-Dual Approach for Policy Learning with SDP Formulations
Han Wang, Feiran Zhao, Florian Dorfler
This paper develops a data-enabled primal-dual framework for learning optimal control policies for unknown linear discrete-time systems from online data. The proposed approach view…
A Coalitional Stable and Fair Reward Allocation for Dynamic Virtual Power Plants
Carl von Holly-Ponientzietz, Saverio Bolognani, Florian Dörfler +1
This paper establishes crucial cooperation criteria for the operation of Dynamic Virtual Power Plants (DVPPs). We propose a control design and reward allocation mechanism to enable…
Load Management of Distribution Systems via Online Dynamic Pricing
Jiarui Yu, Zhiyu He, Wenbin Wang +3
The growing adoption of electric vehicles (EVs) is increasing peak demand in distribution systems, which can threaten grid stability and reduce operational efficiency. Dynamic elec…
Incentive-Based Load Curtailment with Limited Information: A Bilevel Zeroth-Order Learning Approach
Zhisen Jiang, Florian Dörfler, Saverio Bolognani
Incentive-based load curtailment unlocks critical demand-side flexibility but is hindered by the limited knowledge of private user parameters and the inherent nonsmoothness of resp…
Towards Closed-loop Stability of Nonlinear Receding Horizon Games
Sophie Hall, Florian Dörfler, Timm Faulwasser
We analyze Receding Horizon Games without any MPC-like terminal ingredients. We show that recursive feasibility can be inferred from the turnpike phenomenon under mild assumptions.…
A Gray-Box Approach for Decentralized Grid-Equivalent Model Identification
Sanjay Chandrasekaran, Florian Dörfler, Silvia Mastellone
We propose a decentralized, frequency-domain identification algorithm that estimates the grid-equivalent model using local measurements from the perspective of each converter. Sinc…
Optimal Functional Incentives for Control: The Linear-Quadratic Case with Bilinear Incentives
Jonas G. Matt, Saverio Bolognani, Florian Dörfler
We study the design of functional incentive mechanisms for dynamical systems, in which a leader designs a fixed incentive function to motivate a self-interested follower to actuate…
Optimistic Online LQR via Intrinsic Rewards
Marcell Bartos, Bruce D. Lee, Lenart Treven +3
Optimism in the face of uncertainty is a popular approach to balance exploration and exploitation in reinforcement learning. Here, we consider the online linear quadratic regulator…
Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters
Marcell Bartos, Johannes Köhler, Florian Dörfler +1
Standard model-based control design deteriorates when the system dynamics change during operation. To overcome this challenge, online and adaptive methods have been proposed in the…
A Spatially Informed Gaussian Process UCB Method for Decentralized Coverage Control
Gennaro Guidone, Luca Monegaglia, Elia Raimondi +3
We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off between exploration and exploitati…
Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
Taiki Nakano, Ahmed Aboudonia, Jaap Eising +3
We propose data-driven decentralized control algorithms for stabilizing interconnected discrete-time linear time-invariant systems. We first derive a data-driven condition to synth…
A Data-Driven Optimal Control Architecture for Grid-Connected Power Converters
Ruohan Leng, Linbin Huang, Huanhai Xin +4
Grid-connected power converters are ubiquitous in modern power systems, acting as grid interfaces of renewable energy sources, energy storage systems, electric vehicles, high-volta…
A Vision for Trustworthy, Fair, and Efficient Socio-Technical Control using Karma Economies
Ezzat Elokda, Andrea Censi, Emilio Frazzoli +2
Control systems will play a pivotal role in addressing societal-scale challenges as they drive the development of sustainable future smart cities. At the heart of these challenges…