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Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can…

Computers and Society · Computer Science 2017-10-19 David Broman

The ability to robustly and efficiently control the dynamics of nonlinear systems lies at the heart of many current technological challenges, ranging from drug delivery systems to ensuring flight safety. Most such scenarios are too complex…

Fluid Dynamics · Physics 2021-02-16 Radu Cimpeanu , Susana N. Gomes , Demetrios T. Papageorgiou

This paper presents a novel deep learning framework for solving multiple optimal stopping problems in high dimensions. While deep learning has recently shown promise for single stopping problems, the multiple exercise case involves complex…

Optimization and Control · Mathematics 2025-12-30 Mathieu Laurière , Mehdi Talbi

This article demonstrates a new approach to finding ideal bowling targeting strategies through computer simulation. To model bowling ball behaviour, a system of five coupled differential equations is derived using Euler equations for rigid…

Popular Physics · Physics 2022-10-14 Simon Ji , Shouzhuo Yang , Wilber Dominguez , Cacey Bester

Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid…

Formal Languages and Automata Theory · Computer Science 2011-06-08 Davide Bresolin , Marta Capiluppi

This paper deals a continuous-time state-dependent jump linear system, a particular kind of stochastic switching system. In particular, we consider a situation when the transition rate of the random jump process depends on the state…

Systems and Control · Computer Science 2016-11-26 Shaikshavali Chitraganti , Samir Aberkane , Christophe Aubrun

Control of a dynamical system without the knowledge of dynamics is an important and challenging task. Modern machine learning approaches, such as deep neural networks (DNNs), allow for the estimation of a dynamics model from control inputs…

Systems and Control · Electrical Eng. & Systems 2023-11-14 Suruchi Sharma , Volodymyr Makarenko , Gautam Kumar , Stas Tiomkin

In this paper, we present some properties of time optimal controls for linear ODEs with the ball-type control constraint. More precisely, for an optimal control, we build up an upper bound for the number of its switching points; show that…

Optimization and Control · Mathematics 2019-11-19 Shulin Qin , Gengsheng Wang , Huaiqiang Yu

In vehicle dynamics control, many variables of interest cannot be directly measured, as sensors might be costly, fragile, or even not available. Therefore, real-time estimation techniques need to be used. The previous approach suffers from…

Systems and Control · Electrical Eng. & Systems 2023-03-10 Giorgio Riva , Simone Formentin , Matteo Corno , Sergio M. Savaresi

Robotic Hopping is challenging from the perspective of both modeling the dynamics as well as the mechanical design due to the short period of ground contact in which to actuate on the world. Previous work has demonstrated stable hopping on…

Robotics · Computer Science 2019-10-01 Eric Ambrose , Aaron D. Ames

Hybrid dynamical systems are systems which posses both continuous and discrete transitions. Assuming that the discrete transitions (resets) occur a finite number of times, the optimal control problem can be solved by gluing together the…

Optimization and Control · Mathematics 2024-03-20 William Clark , Maria Oprea , Aden Shaw

In this paper we investigate an optimal control problem involving a toy model for the protection on a crop field. Precisely, we consider a protection on a crop field and we want to place intervention zones represented by a control, in order…

Optimization and Control · Mathematics 2025-05-12 Luis Almeida , Aymeric Jacob de Cordemoy , Ayman Moussa , Nicolas Vauchelet

This report describes an approach for simulating multi-body contacts of actively-controlled systems. In this work, we focus on the controls and contact simulation of a 2-dimensional bipedal robot kicking a circular ball.

Robotics · Computer Science 2021-12-17 Alphonsus Adu-Bredu

Research on control using models based on machine-learning methods has now shifted to the practical engineering stage. Achieving high performance and theoretically guaranteeing the safety of the system is critical for such applications. In…

Systems and Control · Electrical Eng. & Systems 2025-01-28 Ryuta Moriyasu , Masayuki Kusunoki , Kenji Kashima

Several scenarios used in teaching feature a rolling motion with slipping that transitions to one without through friction with the ground. We summarise these transitions by introducing an unknown impulse that is transferred to the ground.…

Physics Education · Physics 2021-10-27 Gerrit Ansmann

In-Hand Manipulation, as many other dexterous tasks, remains a difficult challenge in robotics by combining complex dynamic systems with the capability to control and manoeuvre various objects using its actuators. This work presents the…

Robotics · Computer Science 2025-12-15 Alexandre Lopes , Catarina Barata , Plinio Moreno

Robots in dynamic environments need fast, accurate models of how objects move in their environments to support agile planning. In sports such as ping pong, analytical models often struggle to accurately predict ball trajectories with spins…

Robotics · Computer Science 2025-02-24 Qingyu Xiao , Zixuan Wu , Matthew Gombolay

This paper considers the optimal control problem of an extended spring-loaded inverted pendulum (SLIP) model with two additional actuators for active leg length and hip torque modulation. These additional features arise naturally in…

Robotics · Computer Science 2019-11-19 Hua Chen , Patrick M. Wensing , Wei Zhang

This paper is concerned with a bilinear control problem for enhancing convection-cooling via an incompressible velocity field. Both optimal open-loop control and closed-loop feedback control designs are addressed. First and second order…

Optimization and Control · Mathematics 2021-07-15 Weiwei Hu , Jun Liu , Zhu Wang

Several model-based and model-free methods have been proposed for the robot trajectory learning task. Both approaches have their benefits and drawbacks. They can usually complement each other. Many research works are trying to integrate…

Robotics · Computer Science 2020-12-24 Shidi Li