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We propose a novel reformulation of the stochastic optimal control problem as an approximate inference problem, demonstrating, that such a interpretation leads to new practical methods for the original problem. In particular we characterise…

Machine Learning · Computer Science 2010-09-22 Konrad Rawlik , Marc Toussaint , Sethu Vijayakumar

In this work, we present a method for minimizing the time required for a redundant dual-arm robot to follow a desired relative Cartesian path at constant path speed by optimizing its joint trajectories, subject to position, velocity, and…

Robotics · Computer Science 2025-06-05 Jonathan Fried , Santiago Paternain

In this paper, we study the minimal cost constrained input-output (I/O) and control configuration co-design problem. Given a linear time-invariant plant, where a collection of possible inputs and outputs is known a priori, we aim to…

Optimization and Control · Mathematics 2015-03-17 Sergio Pequito , Soummya Kar , George J. Pappas

The aim of the paper is to reduce one spectral optimization problem, which involves the minimization of the decay rate $|\mathrm{Im} \, k |$ of a resonance $k$, to a collection of optimal control problems on the Riemann sphere…

Optimization and Control · Mathematics 2021-04-06 Illya M. Karabash , Herbert Koch , Ievgen V. Verbytskyi

A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of…

Data Structures and Algorithms · Computer Science 2017-05-08 Amgad Madkour , Walid G. Aref , Faizan Ur Rehman , Mohamed Abdur Rahman , Saleh Basalamah

In this paper we consider a control system of the form $\dot x = F(x)u$, linear in the control variable $u$. Given a fixed starting point, we study a finite-horizon optimal control problem, where we want to minimize a weighted sum of an…

Optimization and Control · Mathematics 2023-11-20 Alessandro Scagliotti

A numerical study of an optimal control formulation for a shape optimization problem governed by an elliptic variational inequality is performed. The shape optimization problem is reformulated as a boundary control problem in a fixed…

Optimization and Control · Mathematics 2018-01-22 Raino A. E. Mäkinen

An st-shortest path, or st-path for short, in a graph G is a shortest (induced) path from s to t in G. Two st-paths are said to be adjacent if they differ on exactly one vertex. A reconfiguration sequence between two st-paths P and Q is a…

Computational Complexity · Computer Science 2024-06-19 Nicolas Bousquet , Kshitij Gajjar , Abhiruk Lahiri , Amer E. Mouawad

An optimal control problem with a time-parameter is considered. The functional to be optimized includes the maximum over time-horizon reached by a function of the state variable, and so an $L^\infty$-term. In addition to the classical…

Optimization and Control · Mathematics 2018-11-01 Sébastien Court , Karl Kunisch , Laurent Pfeiffer

We consider a bilinear optimal control problem with pointwise tracking for a semilinear elliptic PDE in two and three dimensions. The control variable enters the PDE as a (reaction) coefficient and the cost functional contains point…

Optimization and Control · Mathematics 2025-12-16 Enrique Otarola , Daniel Quero , Matias Sasso

In recent papers it has been suggested that human locomotion may be modeled as an inverse optimal control problem. In this paradigm, the trajectories are assumed to be solutions of an optimal control problem that has to be determined. We…

Optimization and Control · Mathematics 2010-07-26 Yacine Chitour , Frédéric Jean , Paolo Mason

Distribution Regression on path-space refers to the task of learning functions mapping the law of a stochastic process to a scalar target. The learning procedure based on the notion of path-signature, i.e. a classical transform from rough…

Probability · Mathematics 2023-04-05 Blanka Horvath , Maud Lemercier , Chong Liu , Terry Lyons , Cristopher Salvi

We address the challenge of dimension reduction in the discrete-time optimal control problem which is solved repeatedly online within the framework of model predictive control. Our study demonstrates that a reduced-order approach, aimed at…

Systems and Control · Electrical Eng. & Systems 2024-04-19 Roland Schurig , Andreas Himmel , Rolf Findeisen

In this paper, we study a natural optimal control problem associated to the Paneitz obstacle problem on closed 4-dimensional Riemannian manifolds. We show the existence of an optimal control which is an optimal state and induces also a…

Analysis of PDEs · Mathematics 2022-07-27 Cheikh Birahim Ndiaye

This paper considers linear-quadratic control of a non-linear dynamical system subject to arbitrary cost. I show that for this class of stochastic control problems the non-linear Hamilton-Jacobi-Bellman equation can be transformed into a…

General Physics · Physics 2009-11-11 H. J. Kappen

This paper addresses a continuous-time continuous-space chance-constrained stochastic optimal control (SOC) problem via a Hamilton-Jacobi-Bellman (HJB) partial differential equation (PDE). Through Lagrangian relaxation, we convert the…

Optimization and Control · Mathematics 2022-05-03 Apurva Patil , Alfredo Duarte , Aislinn Smith , Takashi Tanaka , Fabrizio Bisetti

In this paper the computational challenges of time-optimal path following are addressed. The standard approach is to minimize the travel time, which inevitably leads to singularities at zero path speed, when reformulating the optimization…

Robotics · Computer Science 2025-10-24 Tobias Marauli , Hubert Gattringer , Andreas Mueller

The Constraint Shortest Path (CSP) problem is as follows. An $n$-vertex graph is given, each edge/arc assigned two weights. Let us call them "cost" and "length" for definiteness. Finding a min-cost upper-bounded length path between a given…

Data Structures and Algorithms · Computer Science 2022-04-12 Adil Erzin , Roman Plotnikov , Ilya Ladygin

Optimal control techniques provide a means to tailor the control pulses required to generate customized quantum gates, which helps to improve the resilience of quantum simulations to gate errors and device noise. However, the significant…

Given an infeasible, unbounded, or pathological convex optimization problem, a natural question to ask is: what is the smallest change we can make to the problem's parameters such that the problem becomes solvable? In this paper, we address…

Optimization and Control · Mathematics 2020-01-30 Shane Barratt , Guillermo Angeris , Stephen Boyd