English
Related papers

Related papers: Solving differential Riccati equations: A nonlinea…

200 papers

The control algebraic Riccati equation is studied for a class of systems with unbounded control and observation operators. Using a dichotomy property of the associated Hamiltonian operator matrix, two invariant graph subspaces are…

Functional Analysis · Mathematics 2019-07-15 Christian Wyss

Low-rank tensor approximation techniques attempt to mitigate the overwhelming complexity of linear algebra tasks arising from high-dimensional applications. In this work, we study the low-rank approximability of solutions to linear systems…

Numerical Analysis · Mathematics 2016-01-08 Daniel Kressner , André Uschmajew

This paper presents an effective low-rank generalized alternating direction implicit iteration (R-GADI) method for solving large-scale sparse and stable Lyapunov matrix equations and continuous-time algebraic Riccati matrix equations. The…

Numerical Analysis · Mathematics 2024-04-10 Juan Zhang , Wenlu Xun

We consider the numerical solution of the continuous algebraic Riccati equation $A^*X+XA-XFX+G=0$, with $F=F^*, G=G^*$ of low rank and $A$ large and sparse. We develop an algorithm for the low rank approximation of $X$ by means of an…

Numerical Analysis · Mathematics 2013-07-16 Yiding Lin , Valeria Simoncini

We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadratic Regulator (LQR) problems by a learned operator surrogate. Instead of solving a nonlinear…

Optimization and Control · Mathematics 2026-04-22 Jun Chen , Umberto Biccari , Junmin Wang

Low-rank approximation is a technique to approximate a tensor or a matrix with a reduced rank to reduce the memory required and computational cost for simulation. Its broad applications include dimension reduction, signal processing,…

Computational Physics · Physics 2019-06-25 Zhuogang Peng , Ryan G. McClarren , Martin Frank

We consider a stochastic optimal exit time feedback control problem. The Bellman equation is solved approximatively via the Policy Iteration algorithm on a polynomial ansatz space by a sequence of linear equations. As high degree…

Optimization and Control · Mathematics 2020-10-12 Konstantin Fackeldey , Mathias Oster , Leon Sallandt , Reinhold Schneider

This paper is concerned with the convergence of a two-step modified Newton method for solving the nonlinear system arising from the minimal nonnegative solution of nonsymmetric algebraic Riccati equations from neutron transport theory. We…

Numerical Analysis · Mathematics 2025-07-22 Juan Liang , Yonghui Ling

A method to find exact solutions to nonlinear Schr\"odinger equation, defined on a line and on a plane, is found by connecting it with second order linear ordinary differential equation. The connection is essentially made using Riccati…

Exactly Solvable and Integrable Systems · Physics 2014-11-14 Vivek M. Vyas , Rama Gupta , C. N. Kumar , Prasanta K. Panigrahi

A linearized numerical scheme is proposed to solve the nonlinear time fractional parabolic problems with time delay. The scheme is based on the standard Galerkin finite element method in the spatial direction, the fractional Crank-Nicolson…

Numerical Analysis · Mathematics 2021-09-10 Lili Li , Mianfu She , Yuanling Niu

Low-rank tensor approximation approaches have become an important tool in the scientific computing community. The aim is to enable the simulation and analysis of high-dimensional problems which cannot be solved using conventional methods…

Numerical Analysis · Mathematics 2019-02-26 Patrick Gelß , Stefan Klus , Sebastian Matera , Christof Schütte

The low-rank alternating direction implicit (ADI) method is an efficient and effective solver for large-scale standard continuous-time algebraic Riccati equations that admit low-rank solutions. However, the existing low-rank ADI algorithm…

Numerical Analysis · Mathematics 2026-04-16 Umair Zulfiqar

Tensor train (TT) decomposition provides a space-efficient representation for higher-order tensors. Despite its advantage, we face two crucial limitations when we apply the TT decomposition to machine learning problems: the lack of…

Machine Learning · Statistics 2017-08-03 Masaaki Imaizumi , Takanori Maehara , Kohei Hayashi

This paper focuses on the discrete-time backward stochastic linear quadratic (BSLQ) optimal control problem with nonhomogeneous system terms and cost function cross terms. The terminal constraint of such systems distinguishes it from…

Optimization and Control · Mathematics 2026-04-14 Hu Ligui , Meng Qingxin , Tang Maoning

We propose a low-rank tensor approach to approximate linear transport and nonlinear Vlasov solutions and their associated flow maps. The approach takes advantage of the fact that the differential operators in the Vlasov equation is tensor…

Numerical Analysis · Mathematics 2022-03-23 Wei Guo , Jing-Mei Qiu

This study proposes an efficient Newton-type method for the optimal control of switched systems under a given mode sequence. A mesh-refinement-based approach is utilized to discretize continuous-time optimal control problems (OCPs) and…

Optimization and Control · Mathematics 2021-12-21 Sotaro Katayama , Toshiyuki Ohtsuka

We derive closed-form extensions of Riccati's recursions (both sequential and parallel) for solving dual-regularized LQR problems. We show how these methods can be used to solve general constrained, non-convex, discrete-time optimal control…

Optimization and Control · Mathematics 2026-02-26 João Sousa-Pinto , Dominique Orban

The variational field equations of Brans-Dicke scalar-tensor theory of gravitation are given in a non-Riemannian setting in the language of exterior differential forms over 4-dimensional spacetimes. A conformally re-scaled Robinson-Trautman…

General Relativity and Quantum Cosmology · Physics 2019-02-15 Muzaffer Adak , Tekin Dereli , Yorgo Senikoglu

The purpose of this work is the development of space-time discretization schemes for phase-field optimal control problems. First, a time discretization of the forward problem is derived using a discontinuous Galerkin formulation. Here, a…

Optimization and Control · Mathematics 2022-03-24 Denis Khimin , Marc C. Steinbach , Thomas Wick

This paper proposes a new framework for computing low-rank solutions to nonlinear matrix equations arising from spatial discretization of nonlinear partial differential equations: low-rank Anderson acceleration (lrAA). lrAA is an adaptation…

Numerical Analysis · Mathematics 2025-03-25 Daniel Appelo , Yingda Cheng
‹ Prev 1 3 4 5 6 7 10 Next ›