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A computational method for the synthesis of time-optimal feedback control laws for linear nilpotent systems is proposed. The method is based on the use of the bang-bang theorem, which leads to a characterization of the time-optimal…

Optimization and Control · Mathematics 2026-05-20 Sara Bicego , Samuel Gue , Dante Kalise , Nelly Villamizar

The paper addresses an optimal control problem for a perturbed sweeping process of the rate-independent hysteresis type described by a controlled "play and stop" operator with separately controlled perturbations. This problem can be reduced…

Optimization and Control · Mathematics 2015-12-01 Tan H. Cao , Boris S. Mordukhovich

Precise optical phase control is crucial for innovations in telecommunications, optical computing, quantum information processing, and advanced sensing. However, conventional phase modulators often introduce parasitic amplitude modulation…

Optics · Physics 2025-05-23 Alex Krasnok

We present a stochastic trust-region model-based framework in which its radius is related to the probabilistic models. Especially, we propose a specific algorithm, termed STRME, in which the trust-region radius depends linearly on the…

Optimization and Control · Mathematics 2022-09-30 Xiaoyu Wang , Ya-xiang Yuan

This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The proposed approach jointly optimizes a nominal nonlinear…

Systems and Control · Electrical Eng. & Systems 2023-09-14 Antoine P. Leeman , Jerome Sieber , Samir Bennani , Melanie N. Zeilinger

In this paper we study the problem of synthesizing optimal control policies for uncertain continuous-time nonlinear systems from syntactically co-safe linear temporal logic (scLTL) formulas. We formulate this problem as a sequence of…

Systems and Control · Electrical Eng. & Systems 2021-04-16 Max Cohen , Calin Belta

Quantum optimal control represents a powerful technique to enhance the performance of quantum experiments by engineering the controllable parameters of the Hamiltonian. However, the computational overhead for the necessary optimization of…

Feedback optimization refers to a class of methods that steer a control system to a steady state that solves an optimization problem. Despite tremendous progress on the topic, an important problem remains open: enforcing state constraints…

Optimization and Control · Mathematics 2026-02-11 Giannis Delimpaltadakis , Pol Mestres , Jorge Cortés , W. P. M. H. Heemels

For solving large-scale non-convex problems, we propose inexact variants of trust region and adaptive cubic regularization methods, which, to increase efficiency, incorporate various approximations. In particular, in addition to approximate…

Optimization and Control · Mathematics 2018-02-21 Zhewei Yao , Peng Xu , Farbod Roosta-Khorasani , Michael W. Mahoney

In this paper, problems of optimal control are considered where in the objective function, in addition to the control cost there is a tracking term that measures the distance to a desired stationary state. The tracking term is given by some…

Optimization and Control · Mathematics 2020-06-15 Martin Gugat , Michael Schuster , Enrique Zuazua

In this work we investigate a phase field model for damage processes in two-dimensional viscoelastic media with nonhomogeneous Neumann data describing external boundary forces. In the first part we establish global-in-time existence,…

Analysis of PDEs · Mathematics 2016-09-16 M. Hassan Farshbaf-Shaker , Christian Heinemann

In this paper we address the numerical solution of nonlinear ill-posed systems by iterative regularization methods in the classes of Levenberg-Marquardt, trust-region and adaptive quadratic regularization procedures. Both with exact and…

Numerical Analysis · Mathematics 2015-04-17 Stefania Bellavia , Benedetta Morini

We present an efficient transcription method for highly oscillatory optimal control problems. For these problems, the optimal state trajectory consists of fast oscillations that change slowly over the time horizon. Out of a large number of…

Optimization and Control · Mathematics 2022-05-19 Jakob Harzer , Jochem De Schutter , Moritz Diehl

Trust region and cubic regularization methods have demonstrated good performance in small scale non-convex optimization, showing the ability to escape from saddle points. Each iteration of these methods involves computation of gradient,…

Optimization and Control · Mathematics 2018-09-27 Liu Liu , Xuanqing Liu , Cho-Jui Hsieh , Dacheng Tao

Boundary feedback control design is studied for 1D hyperbolic systems with an in-domain disturbance and a boundary feedback controller under the effect of actuator saturation. Nonlinear semigroup theory is used to prove well-posedness of…

Optimization and Control · Mathematics 2022-05-18 Suha Shreim , Francesco Ferrante , Christophe Prieur

The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalism employed herein along with an observational model where…

Machine Learning · Computer Science 2022-09-13 Paul Scharnhorst , Emilio T. Maddalena , Yuning Jiang , Colin N. Jones

In recent years, random subspace methods have been actively studied for large-dimensional nonconvex problems. Recent subspace methods have improved theoretical guarantees such as iteration complexity and local convergence rate while…

Optimization and Control · Mathematics 2025-03-25 Rei Higuchi , Pierre-Louis Poirion , Akiko Takeda

Band-limited functions are fundamental objects that are widely used in systems theory and signal processing. In this paper we refine a recent nonparametric, nonasymptotic method for constructing simultaneous confidence regions for…

Machine Learning · Statistics 2026-01-27 Balázs Csanád Csáji , Bálint Horváth

The paper is concerned with an optimal control problem governed by the rate-independent system of quasi-static perfect elasto-plasticity. The objective is optimize the displacement field in the domain occupied by the body by means of…

Optimization and Control · Mathematics 2020-03-24 Christian Meyer , Stephan Walther

A data-driven model identification strategy is developed for dynamical systems near a supercritical Hopf bifurcation with nonautonomous inputs. This strategy draws on phase-amplitude reduction techniques, leveraging an analytical…

Dynamical Systems · Mathematics 2024-05-07 Dan Wilson