Roy S. Smith
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View article: Network-Independent Incremental Passivity Conditions for Grid-Forming Inverter Control
Network-Independent Incremental Passivity Conditions for Grid-Forming Inverter Control Open
Grid-forming inverters control the power transfer between the AC and DC sides of an electrical grid while maintaining the frequency and voltage of the AC side. This paper focuses on ensuring large-signal stability of an electrical grid wit…
View article: System identification beyond the Nyquist frequency: A kernel-regularized approach
System identification beyond the Nyquist frequency: A kernel-regularized approach Open
Models that contain intersample behavior are important for control design of systems with slow-rate outputs. The aim of this paper is to develop a system identification technique for fast-rate models of systems where only slow-rate output …
View article: Scalable tube model predictive control of uncertain linear systems using ellipsoidal sets
Scalable tube model predictive control of uncertain linear systems using ellipsoidal sets Open
This work proposes a novel robust model predictive control (MPC) algorithm for linear systems affected by dynamic model uncertainty and exogenous disturbances. The uncertainty is modeled using a linear fractional perturbation structure wit…
View article: Plug and Play Distributed Control of Clustered Energy Hub Networks
Plug and Play Distributed Control of Clustered Energy Hub Networks Open
The transition to renewable energy is driving the rise of distributed multi-energy systems, in which individual energy hubs and prosumers (e.g., homes, industrial campuses) generate, store, and trade energy. Economic Model Predictive Contr…
View article: Loss-aware Pricing Strategies for Peer-to-Peer Energy Trading
Loss-aware Pricing Strategies for Peer-to-Peer Energy Trading Open
Peer-to-peer(P2P) energy trading may increase efficiency and reduce costs, but introduces significant challenges for network operators such as maintaining grid reliability, accounting for network losses, and redistributing costs equitably.…
View article: Peak Time-Windowed Mean Estimation using Convex Optimization
Peak Time-Windowed Mean Estimation using Convex Optimization Open
International audience
View article: Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation
Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation Open
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 analyzed. The proposed algorithm uses both absolute and rela…
View article: Data-Driven Structured Robust Control of Linear Systems
Data-Driven Structured Robust Control of Linear Systems Open
Static structured control refers to the task of designing a state-feedback controller such that the control gain satisfies a subspace constraint. Structured control has applications in control of communication-inhibited dynamical systems, …
View article: Peak estimation of rational systems using convex optimization
Peak estimation of rational systems using convex optimization Open
This paper presents algorithms that upper-bound the peak value of a state function along trajectories of a continuous-time system with rational dynamics. The finite-dimensional but nonconvex peak estimation problem is cast as a convex infi…
View article: Peak estimation of rational systems using convex optimization
Peak estimation of rational systems using convex optimization Open
This paper presents algorithms that upper-bound the peak value of a state function along trajectories of a continuous-time system with rational dynamics. The finite-dimensional but nonconvex peak estimation problem is cast as a convex infi…
View article: Online Feedback Equilibrium Seeking
Online Feedback Equilibrium Seeking Open
This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) …
View article: Peak Time-Windowed Risk Estimation of Stochastic Processes
Peak Time-Windowed Risk Estimation of Stochastic Processes Open
This paper develops a method to upper-bound extreme-values of time-windowed risks for stochastic processes. Examples of such risks include the maximum average or 90% quantile of the current along a transmission line in any 5-minute window.…
View article: Finite Sample Frequency Domain Identification
Finite Sample Frequency Domain Identification Open
We study non-parametric frequency-domain system identification from a finite-sample perspective. We assume an open loop scenario where the excitation input is periodic and consider the Empirical Transfer Function Estimate (ETFE), where the…
View article: Small Noise Analysis of Non-Parametric Closed-Loop Identification
Small Noise Analysis of Non-Parametric Closed-Loop Identification Open
We revisit the problem of non-parametric closed-loop identification in frequency domain; we give a brief survey of the literature and provide a small noise analysis of the direct, indirect, and joint input-output methods when two independe…
View article: Optimal Data-Driven Prediction and Predictive Control using Signal Matrix Models
Optimal Data-Driven Prediction and Predictive Control using Signal Matrix Models Open
Data-driven control uses a past signal trajectory to characterise the input-output behaviour of a system. Willems' lemma provides a data-based prediction model allowing a control designer to bypass the step of identifying a state-space or …
View article: Online Identification of Stochastic Continuous-Time Wiener Models Using Sampled Data
Online Identification of Stochastic Continuous-Time Wiener Models Using Sampled Data Open
It is well known that ignoring the presence of stochastic disturbances in the identification of stochastic Wiener models leads to asymptotically biased estimators. On the other hand, optimal statistical identification, via likelihood-based…
View article: Frequency-Domain Identification of Discrete-Time Systems using Sum-of-Rational Optimization
Frequency-Domain Identification of Discrete-Time Systems using Sum-of-Rational Optimization Open
We propose a computationally tractable method for the identification of stable canonical discrete-time rational transfer function models, using frequency domain data. The problem is formulated as a global non-convex optimization problem wh…
View article: MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches
MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches Open
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View article: Stochastic Data-Driven Predictive Control: Regularization, Estimation, and Constraint Tightening
Stochastic Data-Driven Predictive Control: Regularization, Estimation, and Constraint Tightening Open
Data-driven predictive control methods based on the Willems' fundamental lemma have shown great success in recent years. These approaches use receding horizon predictive control with nonparametric data-driven predictors instead of model-ba…
View article: Closed-Loop Identification of Stabilized Models Using Dual Input-Output Parameterization
Closed-Loop Identification of Stabilized Models Using Dual Input-Output Parameterization Open
This paper introduces a dual input-output parameterization (dual IOP) for the identification of linear time-invariant systems from closed-loop data. It draws inspiration from the recent input-output parameterization developed to synthesize…
View article: Data-driven modeling of heat pumps and thermal storage units for MPC
Data-driven modeling of heat pumps and thermal storage units for MPC Open
Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategies, heat pump operation…
View article: Data-driven predictive control for demand side management: Theoretical and experimental results
Data-driven predictive control for demand side management: Theoretical and experimental results Open
Demand side management is perceived as a tool to support a secure and reliable energy system operation amid growing integration of renewable energy resources. However, the lack of scalable modeling and control procedures hinders the practi…
View article: MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches
MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches Open
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 converters. Existing grid impedance measurement approaches typica…
View article: Distributed Multi-Horizon Model Predictive Control for Network of Energy Hubs
Distributed Multi-Horizon Model Predictive Control for Network of Energy Hubs Open
The increasing penetration of renewable energy resources has transformed the energy system from traditional hierarchical energy delivery paradigm to a distributed structure. Such development is accompanied with continuous liberalization in…