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In recent years, a number of tools have become available that recover the underlying control policy from constrained movements. However, few have explicitly considered learning the constraints of the motion and ways to cope with unknown…

Machine Learning · Computer Science 2016-07-27 Hsiu-Chin Lin , Matthew Howard

This work concentrates on a class of optimal control problems for semilinear parabolic equations subject to control constraint of the form $\|u(t)\|_{L^1(\Omega)} \le \gamma$ for $t \in (0,T)$. This limits the total control that can be…

Optimization and Control · Mathematics 2021-12-03 Eduardo Casas , Karl Kunisch

We introduce the concept of a control contraction metric, extending contraction analysis to constructive nonlinear control design. We derive sufficient conditions for exponential stabilizability of all trajectories of a nonlinear control…

Systems and Control · Computer Science 2017-02-09 Ian R. Manchester , Jean-Jacques E. Slotine

This paper addresses the equivalence problem of conic submanifolds in the tangent bundle of a smooth 2-dimensional manifold. Those are given by a quadratic relation between the velocities and are treated as nonholonomic constraints whose…

Optimization and Control · Mathematics 2023-10-03 Timothée Schmoderer , Witold Respondek

The desirable properties when constructing collections of subspaces often include the algebraic constraint that the projections onto the subspaces yield a resolution of the identity like the projections onto lines spanned by vectors of an…

Functional Analysis · Mathematics 2021-06-02 Emily J. King

Data-driven machine learning models often require extensive datasets, which can be costly or inaccessible, and their predictions may fail to comply with established physical laws. Current approaches for incorporating physical priors…

Machine Learning · Computer Science 2025-11-19 Matilde Valente , Tiago C. Dias , Vasco Guerra , Rodrigo Ventura

Recently, diffusion models have been used to solve various inverse problems in an unsupervised manner with appropriate modifications to the sampling process. However, the current solvers, which recursively apply a reverse diffusion step…

Machine Learning · Computer Science 2024-05-21 Hyungjin Chung , Byeongsu Sim , Dohoon Ryu , Jong Chul Ye

In this paper we establish the theory on semiglobal classical solution to first order quasilinear hyperbolic systems with a kind of nonlocal boundary conditions, and based on this, the corresponding exact boundary controllability and…

Optimization and Control · Mathematics 2009-08-11 Tatsien Li , Bopeng Rao , Zhiqiang Wang

This paper is concerned with the existence of optimal controls for backward stochastic partial differential equations with random coefficients, in which the control systems are represented in an abstract evolution form, i.e. backward…

Optimization and Control · Mathematics 2016-12-07 Qingxin Meng , Yang Shen , Peng Shi

We introduce a manifold-based framework for addressing optimization problems with equality and inequality constraints found in robotics. Our approach transforms the original problem into an unconstrained optimization problem directly on the…

Robotics · Computer Science 2026-05-21 Yetong Zhang , Frank Dellaert

Unknown nonlinear dynamics can limit the performance of model-based feedforward control. The aim of this paper is to develop a feedforward control framework for systems with unknown, typically nonlinear, dynamics. To address the unknown…

Systems and Control · Electrical Eng. & Systems 2023-03-31 Johan Kon , Dennis Bruijnen , Jeroen van de Wijdeven , Marcel Heertjes , Tom Oomen

In this paper, motivated by the study of optimal control problems for infinite dimensional systems with endpoint state constraints, we introduce the notion of finite codimensional (exact/approximate) controllability. Some equivalent…

Optimization and Control · Mathematics 2018-10-03 Xu Liu , Qi Lü , Xu Zhang

Robust control of complex engineered and biological systems hinges on the integration of feedforward and feedback mechanisms. This is exemplified in neural motor control, where feedforward muscle co-contraction complements sensory-driven…

Optimization and Control · Mathematics 2026-03-06 Bastien Berret , Frédéric Jean

The collision avoidance constraints are prominent as non-convex, non-differentiable, and challenging when defined in optimization-based motion planning problems. To overcome these issues, this paper presents a novel non-conservative…

Robotics · Computer Science 2024-04-16 Siavash Tavana , Sepideh Faghihi , Anton de Ruiter , Krishna Dev Kumar

Given two arbitrary closed sets in Euclidean space, a simple transversality condition guarantees that the method of alternating projections converges locally, at linear rate, to a point in the intersection. Exact projection onto nonconvex…

Optimization and Control · Mathematics 2018-11-06 Dmitriy Drusvyatskiy , Adrian S. Lewis

The effectiveness of the hyperbolic relaxation method for solving the Einstein constraint equations numerically is studied here on a variety of compact orientable three-manifolds. Convergent numerical solutions are found using this method…

General Relativity and Quantum Cosmology · Physics 2024-03-05 Fan Zhang , Lee Lindblom

Direct methods for the simulation of optimal control problems apply a specific discretization to the dynamics of the problem, and the discrete adjoint method is suitable to calculate corresponding conditions to approximate an optimal…

We use the energy method to study the well-posedness of initial-boundary value problems approximated by overset mesh methods in one and two space dimensions for linear constant-coefficient hyperbolic systems. We show that in one space…

Numerical Analysis · Mathematics 2021-11-24 David A. Kopriva , Jan Nordström , Gregor J. Gassner

A numerical solution scheme for the Einstein field equations based on generalized harmonic coordinates is described, focusing on details not provided before in the literature and that are of particular relevance to the binary black hole…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Frans Pretorius

This paper proposes an intrinsic pseudospectral convexification framework for optimal control problems with manifold constraints. While successive pseudospectral convexification combines spectral collocation with successive convexification,…

Optimization and Control · Mathematics 2025-12-11 Tatsuya Narumi , Shin-ichiro Sakai
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