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Related papers: Strong Formulations for Hybrid System Control

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The mathematical framework of hybrid system is a recent and general tool to treat control systems involving control action of heterogeneous nature. In this paper, we construct and test a semi-Lagrangian numerical scheme for solving the…

Numerical Analysis · Mathematics 2016-08-03 Roberto Ferretti , Achille Sassi

When writing a constraint program, we have to choose which variables should be the decision variables, and how to represent the constraints on these variables. In many cases, there is considerable choice for the decision variables.…

Artificial Intelligence · Computer Science 2011-07-04 B. Hnich , B. M. Smith , T. Walsh

A novel splitting scheme to solve parametric multiconvex programs is presented. It consists of a fixed number of proximal alternating minimisations and a dual update per time step, which makes it attractive in a real-time Nonlinear Model…

Optimization and Control · Mathematics 2014-07-22 Jean-Hubert Hours , Colin N. Jones

This paper presents a novel approach to synthesize dual controllers for unknown linear time-invariant systems with the tasks of optimizing a quadratic cost while reducing the uncertainty. To this end, a synthesis problem is defined where…

Systems and Control · Electrical Eng. & Systems 2021-04-13 Andrea Iannelli , Mohammad Khosravi , Roy S. Smith

We consider homogenization problems in the framework of deterministic optimal control when the dynamics and running costs are completely different in two (or more) complementary domains of the space $\R^N$. For such optimal control…

Analysis of PDEs · Mathematics 2014-05-06 Guy Barles , Ariela Briani , Emmanuel Chasseigne , Nicoletta Tchou

Many nonlinear optimal control and optimization problems involve constraints that combine continuous dynamics with discrete logic conditions. Standard approaches typically rely on mixed-integer programming, which introduces scalability…

Systems and Control · Electrical Eng. & Systems 2026-01-08 Jad Wehbeh , Eric C. Kerrigan

This paper deals with distributed control of microgrids composed of storages, generators, renewable energy sources, critical and controllable loads. We consider a stochastic formulation of the optimal control problem associated to the…

Optimization and Control · Mathematics 2021-06-16 Andrea Camisa , Giuseppe Notarstefano

This paper presents a mixed-integer quadratic programming formulation of an existing data-driven approach to computational elasticity. This formulation is suitable for application of a standard mixed-integer programming solver, which finds…

Optimization and Control · Mathematics 2019-09-17 Yoshihiro Kanno

This paper surveys the primary computational hurdles of Energy Systems optimization coming from different sources: model-induced complexity, optimization algorithm requirements, and uncertainties handling (both aleatoric and epistemic).…

We consider the numerical integration of non-autonomous separable parabolic equations using high order splitting methods with complex coefficients (methods with real coefficients of order greater than two necessarily have negative…

Numerical Analysis · Mathematics 2014-05-20 Muaz Seydaoğlu , Sergio Blanes

This paper presents a trajectory generation method that optimizes a quadratic cost functional with respect to linear system dynamics and to linear input and state constraints. The method is based on continuous-time flatness-based trajectory…

Systems and Control · Computer Science 2012-11-27 Jean-Francois Stumper , Ralph Kennel

This paper presents a novel factor graph-based approach to solve the discrete-time finite-horizon Linear Quadratic Regulator problem subject to auxiliary linear equality constraints within and across time steps. We represent such optimal…

Robotics · Computer Science 2021-10-27 Shuo Yang , Gerry Chen , Yetong Zhang , Howie Choset , Frank Dellaert

Quadratic programming is a workhorse of modern nonlinear optimization, control, and data science. Although regularized methods offer convergence guarantees under minimal assumptions on the problem data, they can exhibit the slow…

Optimization and Control · Mathematics 2026-05-18 Jeremy Bertoncini , Alberto De Marchi , Matthias Gerdts , Simon Gottschalk

Hybrid systems are a compact and natural mechanism with which to address problems in robotics. This work introduces an approach to learning hybrid systems from demonstrations, with an emphasis on extracting models that are explicitly…

Robotics · Computer Science 2019-09-12 Michael Burke , Svetlin Penkov , Subramanian Ramamoorthy

In this paper, we extend the idea of using controlled perturbations to enhance the capabilities of active-set prediction for interior point methods for convex Quadratic Programming (QP) problems. Namely, we consider perturbing the…

Optimization and Control · Mathematics 2014-09-23 Yiming Yan

We present a hybrid algorithm for optimizing a convex, smooth function over the cone of positive semidefinite matrices. Our algorithm converges to the global optimal solution and can be used to solve general large-scale semidefinite…

Machine Learning · Computer Science 2012-06-22 Soeren Laue

We consider the constrained assortment optimization problem under the mixed multinomial logit model. Even moderately sized instances of this problem are challenging to solve directly using standard mixed-integer linear optimization…

Optimization and Control · Mathematics 2017-08-15 Alper Sen , Alper Atamturk , Philip Kaminsky

We consider the optimal control problem for a linear conditional McKean-Vlasov equation with quadratic cost functional. The coefficients of the system and the weigh-ting matrices in the cost functional are allowed to be adapted processes…

Probability · Mathematics 2017-03-09 Huyên Pham

This note presents an embedded automatic control strategy for a low consumption vehicle equipped with an "on/off" engine. The main difficulties are the hybrid nature of the dynamics, the non smoothness of the dynamics of each mode, the…

Optimization and Control · Mathematics 2017-07-26 Thomas Chambrion , Gilles Millerioux

In this work, we propose an output-feedback tube-based model predictive control (MPC) scheme for linear systems under dynamic uncertainties that are described via integral quadratic constraints (IQC). By leveraging IQCs, a large class of…

Systems and Control · Electrical Eng. & Systems 2025-08-26 Lukas Schwenkel , Johannes Köhler , Matthias A. Müller , Frank Allgöwer
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