1.2k citations · 2.2k across the 51 of their papers we have counts for
56 papers
Krylov Subspace Acceleration for First-Order Splitting Methods in Convex Quadratic Programming
Gabriel Berk Pereira, Paul J. Goulart
We propose an acceleration scheme for first-order methods (FOMs) for convex quadratic programs (QPs) that is analogous to Anderson acceleration and the Generalized Minimal Residual…
A neural network-based approach to hybrid systems identification for control
Filippo Fabiani, Bartolomeo Stellato, Daniele Masti +1
We consider the problem of designing a machine learning-based model of an unknown dynamical system from a finite number of (state-input)-successor state data points, such that the…
Control of Cross-Directional Systems using the Generalised Singular Value Decomposition
Idris Kempf, Paul J. Goulart, Stephen Duncan
Diamond Light Source produces synchrotron radiation by accelerating electrons to relativistic speeds. In order to maximise the intensity of the radiation, vibrations of the electro…
Control of Cross-Directional Systems with Approximate Symmetries
Idris Kempf, Paul Goulart, Stephen Duncan
Structural symmetries of linear dynamical systems can be exploited for decoupling the dynamics and reducing the computational complexity of the controller implementation. However,…
The Past Does Matter: Correlation of Subsequent States in Trajectory Predictions of Gaussian Process Models
Steffen Ridderbusch, Sina Ober-Blöbaum, Paul Goulart
Computing the distribution of trajectories from a Gaussian Process model of a dynamical system is an important challenge in utilizing such models. Motivated by the computational co…
Safeguarded Anderson acceleration for parametric nonexpansive operators
Michael Garstka, Mark Cannon, Paul Goulart
This paper describes the design of a safeguarding scheme for Anderson acceleration to improve its practical performance and stability when used for first-order optimisation methods…
Personalized incentives as feedback design in generalized Nash equilibrium problems
Filippo Fabiani, Andrea Simonetto, Paul J. Goulart
We investigate both stationary and time-varying, nonmonotone generalized Nash equilibrium problems that exhibit symmetric interactions among the agents, which are known to be poten…
Reliably-stabilizing piecewise-affine neural network controllers
Filippo Fabiani, Paul J. Goulart
A common problem affecting neural network (NN) approximations of model predictive control (MPC) policies is the lack of analytical tools to assess the stability of the closed-loop…
Learning equilibria with personalized incentives in a class of nonmonotone games
Filippo Fabiani, Andrea Simonetto, Paul J. Goulart
We consider quadratic, nonmonotone generalized Nash equilibrium problems with symmetric interactions among the agents. Albeit this class of games is known to admit a potential func…
Model Predictive Control for Electron Beam Stabilization in a Synchrotron
Idris Kempf, Paul J. Goulart, Stephen R. Duncan
Electron beam stabilization in a synchrotron is a disturbance rejection problem, with hundreds of inputs and outputs, that is sampled at frequencies higher than kHz. In this f…
Probabilistic stabilizability certificates for a class of black-box linear systems
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We provide out-of-sample certificates on the controlled invariance property of a given set with respect to a class of black-box linear systems. Specifically, we consider linear tim…
A Higher-Order Generalized Singular Value Decomposition for Rank Deficient Matrices
Idris Kempf, Paul J. Goulart, Stephen R. Duncan
The higher-order generalized singular value decomposition (HO-GSVD) is a matrix factorization technique that extends the GSVD to data matrices, and can be used to identif…
Learning ODE Models with Qualitative Structure Using Gaussian Processes
Steffen Ridderbusch, Christian Offen, Sina Ober-Blöbaum +1
Recent advances in learning techniques have enabled the modelling of dynamical systems for scientific and engineering applications directly from data. However, in many contexts exp…
Stochastic output feedback MPC with intermittent observations
Shuhao Yan, Mark Cannon, Paul J. Goulart
This paper designs a model predictive control (MPC) law for constrained linear systems with stochastic additive disturbances and noisy measurements, minimising a discounted cost su…
Multi-Array Electron Beam Stabilization using Block-Circulant Transformation and Generalized Singular Value Decomposition
Idris Kempf, Stephen R. Duncan, Paul J. Goulart +1
We introduce a novel structured controller design for the electron beam stabilization problem of the UK's national synchrotron light source. Because changes to the synchrotron will…
Symmetry Exploitation in Orbit Feedback Systems of Synchrotron Storage Rings
Idris Kempf, Paul J. Goulart, Stephen R. Duncan +1
Structural symmetries in the storage ring of synchrotrons are intentionally created during the design phase of the magnetic lattices, but they are not considered in the design of c…
Approximate Dynamic Programming for Delivery Time Slot Pricing: a Sensitivity Analysis
Denis Lebedev, Kostas Margellos, Paul Goulart
We consider the revenue management problem of finding profit-maximising prices for delivery time slots in the context of attended home delivery. This multi-stage optimal control pr…
Stochastic MPC with Dynamic Feedback Gain Selection and Discounted Probabilistic Constraints
Shuhao Yan, Paul J. Goulart, Mark Cannon
This paper considers linear discrete-time systems with additive disturbances, and designs a Model Predictive Control (MPC) law incorporating a dynamic feedback gain to minimise a q…
Gradient-Bounded Dynamic Programming for Submodular and Concave Extensible Value Functions with Probabilistic Performance Guarantees
Denis Lebedev, Paul Goulart, Kostas Margellos
We consider stochastic dynamic programming problems with high-dimensional, discrete state-spaces and finite, discrete-time horizons that prohibit direct computation of the value fu…
Gradient-Bounded Dynamic Programming with Submodular and Concave Extensible Value Functions
Denis Lebedev, Paul Goulart, Kostas Margellos
We consider dynamic programming problems with finite, discrete-time horizons and prohibitively high-dimensional, discrete state-spaces for direct computation of the value function…
On the robustness of equilibria in generalized aggregative games
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We address the problem of assessing the robustness of the equilibria in uncertain, multi-agent games. Specifically, we focus on generalized Nash equilibrium problems in aggregative…
Output feedback stochastic MPC with packet losses
Shuhao Yan, Mark Cannon, Paul Goulart
The paper considers constrained linear systems with stochastic additive disturbances and noisy measurements transmitted over a lossy communication channel. We propose a model predi…
Probabilistic feasibility guarantees for solution sets to uncertain variational inequalities
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We develop a data-driven approach to the computation of a-posteriori feasibility certificates to the solution sets of variational inequalities affected by uncertainty. Specifically…
The optimal transport paradigm enables data compression in data-driven robust control
Filippo Fabiani, Paul J. Goulart
A new data-enabled control technique for uncertain linear time-invariant systems, recently conceived by Coulson et\ al., builds upon the direct optimization of controllers over inp…