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The core of the Model Predictive Control (MPC) method in every step of the algorithm consists in solving a time-dependent optimization problem on the prediction horizon of the MPC algorithm, and then to apply a portion of the optimal…

Optimization and Control · Mathematics 2021-01-15 Alessandro Alla , Carmen Gräßle , Michael Hinze

In the context of adaptive optics for astronomy, one can rely on the statistics of the turbulent phase to assess a part of the system's performance. Temporal statistics with one source and spatial statistics with two sources are well-known…

Instrumentation and Methods for Astrophysics · Physics 2022-09-05 Cédric Plantet , Giulia Carlà , Guido Agapito , Lorenzo Busoni

Numerical simulations of atmospheric turbulence and AO wavefront correction are performed to investigate the timescale for fringe motion in optical interferometers with spatial filters. These simulations focus especially on partial AO…

Astrophysics · Physics 2009-11-11 Robert Tubbs

Atmospheric turbulence causes fluctuations in the local refractive index of air that accumulatively disturb a wave's phase and amplitude distribution as it propagates. This impairs the effective range of laser weapons as well as the…

Optics · Physics 2015-06-02 Chensheng Wu , Jonathan Ko , Christopher C. Davis

Predicting the output of a dynamical system from streaming data is fundamental to real-time feedback control and decision-making. We first derive an autoregressive representation that relates future local outputs to asynchronous past…

Systems and Control · Electrical Eng. & Systems 2026-03-09 Jiachen Qian , Yang Zheng

This paper introduces a new algorithm to improve the accuracy of numerical phase-averaging in oscillatory, multiscale, differential equations. Phase-averaging is a timestepping method which averages a mapped variable to remove highly…

Numerical Analysis · Mathematics 2024-11-07 Timothy C. Andrews , Beth A. Wingate

We consider the problem setting of prediction with expert advice with possibly heavy-tailed losses, i.e. the only assumption on the losses is an upper bound on their second moments, denoted by $\theta$. We develop adaptive algorithms that…

Machine Learning · Computer Science 2026-01-09 Antoine Moulin , Emmanuel Esposito , Dirk van der Hoeven

We present safe control of partially-observed linear time-varying systems in the presence of unknown and unpredictable process and measurement noise. We introduce a control algorithm that minimizes dynamic regret, i.e., that minimizes the…

Systems and Control · Electrical Eng. & Systems 2023-04-03 Hongyu Zhou , Vasileios Tzoumas

The forecast on a time scale of 1 or 2 hours is crucial for all kind of new generation facilities (ELTs) instrumentation supported by the adaptive optics that will be mainly operated in Service Mode. In a recent study (Masciadri et al.…

Instrumentation and Methods for Astrophysics · Physics 2023-08-08 Elena Masciadri , Alessio Turchi , Luca Fini

When building linear or nonlinear models one is faced with the problem of selecting the best set of variable with which to predict the future dynamics. In nonlinear time series analysis the problem is to select the correct time delays in…

Chaotic Dynamics · Physics 2007-05-23 Michael Small

We introduce an analytical approach that allows predictions and mechanistic insights into the dynamics of nonlinear oscillator networks with heterogeneous time delays. We demonstrate that time delays shape the spectrum of a matrix…

In this paper, the tracking control problem of an Euler-Lagrange system is addressed with regard to parametric uncertainties, and an adaptive-robust control strategy, christened Time-Delayed Adaptive Robust Control (TARC), is presented.…

Systems and Control · Computer Science 2018-05-10 Spandan Roy , Indra Narayan Kar , Jinoh Lee , Nikos Tsagarakis , Darwin G. Caldwell

Classical optimization theory deals with fixed, time-invariant objective functions. However, time-varying optimization has emerged as an important subject for decision-making in dynamic environments. In this work, we study the problem of…

Machine Learning · Computer Science 2025-10-16 Muhammad Faraz Ul Abrar , Nicolò Michelusi , Erik G. Larsson

Decentralized online convex optimization (D-OCO), where multiple agents within a network collaboratively learn optimal decisions in real-time, arises naturally in applications such as federated learning, sensor networks, and multi-agent…

Machine Learning · Statistics 2026-01-14 Hao Qiu , Mengxiao Zhang , Juliette Achddou

Adaptive optics (AO) is critical in astronomy, optical communications and remote sensing to deal with the rapid blurring caused by the Earth's turbulent atmosphere. But current AO systems are limited by their wavefront sensors, which need…

Instrumentation and Methods for Astrophysics · Physics 2020-10-23 Barnaby R. M. Norris , Jin Wei , Christopher H. Betters , Alison Wong , Sergio G. Leon-Saval

In this paper, we provide a general framework for studying multi-agent online learning problems in the presence of delays and asynchronicities. Specifically, we propose and analyze a class of adaptive dual averaging schemes in which agents…

Machine Learning · Computer Science 2022-04-19 Yu-Guan Hsieh , Franck Iutzeler , Jérôme Malick , Panayotis Mertikopoulos

In traditional topology optimization, the computing time required to iteratively update the material distribution within a design domain strongly depends on the complexity or size of the problem, limiting its application in real engineering…

Computational Engineering, Finance, and Science · Computer Science 2024-05-14 Gabriel Garayalde , Matteo Torzoni , Matteo Bruggi , Alberto Corigliano

Accurate delay-Doppler channel estimation is critical for next-evolution waveforms (NEWs) to enable reliable signal detection. This paper proposes a robust channel estimation algorithm that integrates Flag sequences optimized via an…

Signal Processing · Electrical Eng. & Systems 2026-03-17 Yuan Liu , Yilin Qi , Caiqin Li , Haoran Yin , Yanqun Tang , Yao Ge

Dispersive delays due to the Solar wind introduce excess noise in high-precision pulsar timing experiments, and must be removed in order to achieve the accuracy needed to detect, e.g., low-frequency gravitational waves. In current pulsar…

We present the laboratory verification of a method for re- moving the effects of frozen-flow atmospheric turbulence using a Linear Quadratic Gaussian (LQG) controller, also known as a Kalman Filter. This method, which we term "Predictive…

Instrumentation and Methods for Astrophysics · Physics 2015-04-16 Alexander Rudy , Lisa Poyneer , Srikar Srinath , S. Mark Ammons , Donald Gavel
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