Florian Dörfler
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View article: SOMBRL: Scalable and Optimistic Model-Based RL
SOMBRL: Scalable and Optimistic Model-Based RL Open
We address the challenge of efficient exploration in model-based reinforcement learning (MBRL), where the system dynamics are unknown and the RL agent must learn directly from online interactions. We propose Scalable and Optimistic MBRL (S…
View article: Maximum likelihood inference for high-dimensional problems with multiaffine variable relations
Maximum likelihood inference for high-dimensional problems with multiaffine variable relations Open
View article: Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters
Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters Open
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 literature. In this work, we consider the class of discret…
View article: Convergence Analysis of Distributed Optimization: A Dissipativity Framework
Convergence Analysis of Distributed Optimization: A Dissipativity Framework Open
We develop a system-theoretic framework for the structured analysis of distributed optimization algorithms. We model such algorithms as a network of interacting dynamical systems and derive tests for convergence based on incremental dissip…
View article: Dispatchable Current Source Virtual Oscillator Control Achieving Global Stability
Dispatchable Current Source Virtual Oscillator Control Achieving Global Stability Open
This work introduces a novel dispatchable current source virtual oscillator control (dCVOC) scheme for grid-following (GFL) converters, which exhibits duality with dispatchable virtual oscillator control (dVOC) in two ways: a) the current …
View article: Quantifying Grid-Forming Behavior: Bridging Device-Level Dynamics and System-Level Strength
Quantifying Grid-Forming Behavior: Bridging Device-Level Dynamics and System-Level Strength Open
Grid-forming (GFM) technology is widely regarded as a promising solution for future power systems dominated by power electronics. However, a precise method for quantifying GFM converter behavior and a universally accepted GFM definition re…
View article: Ultrafast Grid Impedance Identification in $dq$-Asymmetric Three-Phase Power Systems
Ultrafast Grid Impedance Identification in $dq$-Asymmetric Three-Phase Power Systems Open
We propose a non-parametric frequency-domain method to identify small-signal $dq$-asymmetric grid impedances, over a wide frequency band, using grid-connected converters. Existing identification methods are faced with significant trade-off…
View article: Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems Open
We propose data-driven decentralized control algorithms for stabilizing interconnected systems. We first derive a data-driven condition to synthesize a local controller that ensures the dissipativity of the local subsystems. Then, we propo…
View article: Simulation Priors for Data-Efficient Deep Learning
Simulation Priors for Data-Efficient Deep Learning Open
How do we enable AI systems to efficiently learn in the real-world? First-principles models are widely used to simulate natural systems, but often fail to capture real-world complexity due to simplifying assumptions. In contrast, deep lear…
View article: Distributed time-varying Gaussian process regression via Kalman filtering
Distributed time-varying Gaussian process regression via Kalman filtering Open
View article: Geometric Decentralized Stability Certificate for Power Systems Based on Projecting DW Shells
Geometric Decentralized Stability Certificate for Power Systems Based on Projecting DW Shells Open
The development of decentralized stability conditions has gained considerable attention due to the need to analyze multi-agent network systems, such as heterogeneous multi-converter power systems. A recent advance is the application of the…
View article: DeePConverter: A Data-Driven Optimal Control Architecture for Grid-Connected Power Converters
DeePConverter: A Data-Driven Optimal Control Architecture for Grid-Connected Power Converters Open
Grid-connected power converters are ubiquitous in modern power systems, acting as grid interfaces of renewable energy sources, energy storage systems, electric vehicles, high-voltage DC systems, etc. Conventionally, power converters use mu…
View article: A Markov Decision Process Framework for Early Maneuver Decisions in Satellite Collision Avoidance
A Markov Decision Process Framework for Early Maneuver Decisions in Satellite Collision Avoidance Open
This work presents a Markov decision process (MDP) framework to model decision-making for collision avoidance maneuver (CAM) and a reinforcement learning policy gradient (RL-PG) algorithm to train an autonomous guidance policy using histor…
View article: A stability condition for online feedback optimization without timescale separation
A stability condition for online feedback optimization without timescale separation Open
View article: Convergence and Robustness Bounds for Distributed Asynchronous Shortest-Path
Convergence and Robustness Bounds for Distributed Asynchronous Shortest-Path Open
This work analyzes convergence times and robustness bounds for asynchronous distributed shortest-path computation. We focus on the Adaptive Bellman--Ford algorithm, a self-stabilizing method in which each agent updates its shortest-path es…
View article: Recursive-ARX for Grid-Edge Fault Detection
Recursive-ARX for Grid-Edge Fault Detection Open
Future electrical grids will require new ways to identify faults as inverters are not capable of supplying large fault currents to support existing fault detection methods and because distributed resources may feed faults from the edge of …
View article: Split-as-a-Pro: behavioral control via operator splitting and alternating projections
Split-as-a-Pro: behavioral control via operator splitting and alternating projections Open
The paper introduces Split-as-a-Pro, a control framework that integrates behavioral systems theory, operator splitting methods, and alternating projection algorithms. The framework reduces dynamic optimization problems - arising in both co…
View article: Policy Gradient Adaptive Control for the LQR: Indirect and Direct Approaches
Policy Gradient Adaptive Control for the LQR: Indirect and Direct Approaches Open
Motivated by recent advances of reinforcement learning and direct data-driven control, we propose policy gradient adaptive control (PGAC) for the linear quadratic regulator (LQR), which uses online closed-loop data to improve the control p…
View article: Gaussian behaviors: representations and data-driven control
Gaussian behaviors: representations and data-driven control Open
We propose a modeling framework for stochastic systems, termed Gaussian behaviors, that describes finite-length trajectories of a system as a Gaussian process. The proposed model naturally quantifies the uncertainty in the trajectories, ye…
View article: PRIME: Fast Primal-Dual Feedback Optimization for Markets with Application to Optimal Power Flow
PRIME: Fast Primal-Dual Feedback Optimization for Markets with Application to Optimal Power Flow Open
Online Feedback Optimization (OFO) controllers iteratively drive a plant to an optimal operating point that satisfies input and output constraints, relying solely on the input-output sensitivity as model information. This paper introduces …
View article: The Limits of Fairness of the Variational Generalized Nash Equilibrium
The Limits of Fairness of the Variational Generalized Nash Equilibrium Open
Generalized Nash equilibrium (GNE) problems are commonly used to model strategic interactions between self-interested agents who are coupled in cost and constraints. Specifically, the variational GNE, a refinement of the GNE, is often sele…
View article: System Level Synthesis for Affine Control Policies: Model Based and Data-Driven Settings
System Level Synthesis for Affine Control Policies: Model Based and Data-Driven Settings Open
There is an increasing need for effective control of systems with complex dynamics, particularly through data-driven approaches. System Level Synthesis (SLS) has emerged as a powerful framework that facilitates the control of large-scale s…
View article: Choose Wisely: Data-driven Predictive Control for Nonlinear Systems Using Online Data Selection
Choose Wisely: Data-driven Predictive Control for Nonlinear Systems Using Online Data Selection Open
This paper proposes Select-Data-driven Predictive Control (Select-DPC), a new method for controlling nonlinear systems using output-feedback for which data are available but an explicit model is not. At each timestep, Select-DPC employs on…
View article: Hypergraph reconstruction from dynamics
Hypergraph reconstruction from dynamics Open
A plethora of methods have been developed in the past two decades to infer the underlying network structure of an interconnected system from its collective dynamics. However, methods capable of inferring nonpairwise interactions are only s…
View article: Data-Driven Control for Constant-Temperature Fast Charging of Lithium-Ion Cells
Data-Driven Control for Constant-Temperature Fast Charging of Lithium-Ion Cells Open
View article: Safety Filter for Limiting the Current of Grid-Forming Matrix Modular Multilevel Converters
Safety Filter for Limiting the Current of Grid-Forming Matrix Modular Multilevel Converters Open
Grid-forming (GFM) converters face significant challenges in limiting current during transient grid events while preserving their grid-forming behavior. This paper offers an elegant solution to the problem with a priori guarantees, present…
View article: Regularization for Covariance Parameterization of Direct Data-Driven LQR Control
Regularization for Covariance Parameterization of Direct Data-Driven LQR Control Open
As the benchmark of data-driven control methods, the linear quadratic regulator (LQR) problem has gained significant attention. A growing trend is direct LQR design, which finds the optimal LQR gain directly from raw data and bypassing sys…
View article: An Adaptive Data-Enabled Policy Optimization Approach for Autonomous Bicycle Control
An Adaptive Data-Enabled Policy Optimization Approach for Autonomous Bicycle Control Open
This paper presents a unified control framework that integrates a Feedback Linearization (FL) controller in the inner loop with an adaptive Data-Enabled Policy Optimization (DeePO) controller in the outer loop to balance an autonomous bicy…
View article: First-Order Conditions for Optimization in the Wasserstein Space
First-Order Conditions for Optimization in the Wasserstein Space Open
View article: Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design Open
Although social networks have expanded the range of ideas and information accessible to users, they are also criticized for amplifying the polarization of user opinions. Given the inherent complexity of these phenomena, existing approaches…