From the 1 of 9 linked papers with an AI index.
7 papers · 1 filter
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…
DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization
Michael Cummins, Alberto Padoan, Keith Moffat +2
This paper introduces Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization (DeePC-Hunt), a backpropagation-based method for automatic hyperparamete…
Split-as-a-Pro: behavioral control via operator splitting and alternating projections
Yu Tang, Carlo Cenedese, Alessio Rimoldi +3
The paper introduces Split-as-a-Pro, a control framework that integrates behavioral systems theory, operator splitting methods, and alternating projection algorithms. The framework…
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
Colin Dirren, Mattia Bianchi, Panagiotis D. Grontas +2
We study the convex-concave bilinear saddle-point problem , where both, only one, or none of the functions and are strongly convex, a…
Distributionally Robust Infinite-horizon Control: from a pool of samples to the design of dependable controllers
Jean-Sébastien Brouillon, Andrea Martin, John Lygeros +2
We study control of constrained linear systems with only partial statistical information about the uncertainty affecting the system dynamics and the sensor measurements. Specifical…
Data-Driven Distributionally Robust System Level Synthesis
Francesco Micheli, Anastasios Tsiamis, John Lygeros
We present a novel approach for the control of uncertain, linear time-invariant systems, which are perturbed by potentially unbounded, additive disturbances. We propose a \emph{dou…