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Robot navigation around humans can be a challenging problem since human movements are hard to predict. Stochastic model predictive control (MPC) can account for such uncertainties and approximately bound the probability of a collision to…

Robotics · Computer Science 2024-07-22 Yunfan Gao , Florian Messerer , Niels van Duijkeren , Moritz Diehl

We study a system of interacting particles in the presence of the relativistic kinetic energy, external confining potentials, singular repulsive forces as well as a random perturbation through an additive white noise. In comparison with the…

Probability · Mathematics 2026-05-21 Manh Hong Duong , Hung Dang Nguyen

Problem of damping of an arbitrary number of linear oscillators under common bounded control is considered. We are looking for a feedback control steering the system to the equilibrium. The obtained control is asymptotically optimal: the…

Optimization and Control · Mathematics 2016-12-02 Alexander Ovseevich , Aleksey Fedorov

In the design of complex quantum systems like ion traps for quantum computing, it is usually desired to stabilize a particular system state or make the system state track a desired trajectory. Several control theoretical approaches based on…

Systems and Control · Computer Science 2012-11-26 K. P. Nagarjun , S. Sivaranjani , George Koshy

The well-known generalization problem hinders the application of artificial neural networks in continuous-time prediction tasks with varying latent dynamics. In sharp contrast, biological systems can neatly adapt to evolving environments…

Machine Learning · Computer Science 2025-03-10 Jindou Jia , Zihan Yang , Meng Wang , Kexin Guo , Jianfei Yang , Xiang Yu , Lei Guo

In this paper, inspired by quantum field theory, or more specifically QED, we propose a dynamical model for relativity. By adopting the approach provided by this dynamical model, we provide a dynamical explanation for relativistic phenomena…

General Physics · Physics 2023-05-26 İnanç Şahin

The second law of thermodynamics is discussed and reformulated from a quantum information theoretic perspective for open quantum systems using relative entropy. Specifically, the relative entropy of a quantum state with respect to…

Quantum Physics · Physics 2020-11-11 Neil Dowling , Stefan Floerchinger , Tobias Haas

Optimal control of stochastic nonlinear dynamical systems is a major challenge in the domain of robot learning. Given the intractability of the global control problem, state-of-the-art algorithms focus on approximate sequential optimization…

Machine Learning · Computer Science 2020-04-23 Joe Watson , Hany Abdulsamad , Jan Peters

Quantum control is concerned with active manipulation of physical and chemical processes on the atomic and molecular scale. This work presents a perspective of progress in the field of control over quantum phenomena, tracing the evolution…

Quantum Physics · Physics 2010-07-20 Constantin Brif , Raj Chakrabarti , Herschel Rabitz

Symmetries of nonlinear control systems in state representation are considered. To this end, a geometric approach to ordinary differential equations is advocated. Invariant feedback laws for systems with Lie symmetries, i.e. feedback laws…

Optimization and Control · Mathematics 2012-06-22 Carsten Collon , Joachim Rudolph

Probabilistic control design is founded on the principle that a rational agent attempts to match modelled with an arbitrary desired closed-loop system trajectory density. The framework was originally proposed as a tractable alternative to…

Machine Learning · Computer Science 2023-11-16 Tom Lefebvre

Cosmological perturbations with wavelengths smaller than Hubble radius can be handled in the context of Newtonian theory with very high accuracy. The application of this Newtonian approximation, however, is restricted to nonrelativistic…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Ali Nayeri , T. Padmanabhan

We investigate feedback control of linear quantum systems subject to feedback-loop time delays. In particular, we examine the relation between the potentially achievable control performance and the time delays, and provide theoretical…

Quantum Physics · Physics 2013-05-29 Kazunori Nishio , Kenji Kashima , Jun-ichi Imura

In teaching the physical sciences, a significant challenge lies in the student's tendency to consider the scientific world and the "real" world as separate. For example, Newton's 1st Law of Motion states that an object in motion remains in…

Physics Education · Physics 2007-06-20 Richard P. Barber , David J. Popalisky , Rose Hacking , Kristina Chiapella

Obtaining reliable state preparation protocols is a key step towards practical implementation of many quantum technologies, and one of the main tasks in quantum control. In this work, different reinforcement learning approaches are used to…

Quantum Physics · Physics 2024-09-04 Manuel Guatto , Gian Antonio Susto , Francesco Ticozzi

A dynamical system is a transformation of a phase space, and the transformation law is the primary means of defining as well as identifying the dynamical system. It is the object of focus of many learning techniques. Yet there are many…

Dynamical Systems · Mathematics 2025-02-07 Tyrus Berry , Suddhasattwa Das

The conceptually new approach based on the logarithmic norm to design of robust adaptive state-feedback controller for linear time-varying (LTV) systems under system's modeling uncertainty and nonlinear external disturbance is proposed.…

Optimization and Control · Mathematics 2020-12-18 Robert Vrabel

We consider a hypothetical possibility of the variability of light velocity with time and position in space which is derived from two natural postulates. For the consistent consideration of such variability we generalize translational…

Astrophysics · Physics 2016-08-30 Sergey S. Stepanov

The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering. In this paper we build on the ideas presented by…

Quantum Physics · Physics 2017-08-02 John E. Gough

In this paper, we examine the exact linearization of configuration flat Lagrangian control systems in generalized state representation with p degrees of freedom and p-1 control inputs by quasi-static feedback of its generalized state. We…

Dynamical Systems · Mathematics 2024-11-05 Georg Hartl , Conrad Gstöttner , Bernd Kolar , Markus Schöberl