Data-driven approximations of dynamical systems operators for control

E Kaiser, JN Kutz, SL Brunton - The Koopman operator in systems and …, 2020‏ - Springer
Abstract The Koopman and Perron Frobenius transport operators are fundamentally
changing how we approach dynamical systems, providing linear representations for even …

[ספר][B] Smart autonomous aircraft: flight control and planning for UAV

YB Sebbane - 2015‏ - books.google.com
Smart Autonomous Aircraft: Flight Control and Planning for UAV introduces the advanced
methods of flight control, planning, situation awareness, and decision making. This book is …

Koopman operator approach to optimal control selection under uncertainty

JJ Meyers, AM Leonard, JD Rogers… - 2019 American …, 2019‏ - ieeexplore.ieee.org
Uncertainty propagation is an important step in the derivation of optimal control strategies for
dynamic systems in the presence of state and parameter uncertainty. Many stochastic …

Mars entry navigation with uncertain parameters based on desensitized extended Kalman filter

L Wang, Y **a - IEEE Transactions on Industrial Informatics, 2015‏ - ieeexplore.ieee.org
Mars entry phase is the most challenging part among Mars entry, descent, and landing
(EDL). One of the main reasons is that the lander suffers tough tests from the uncertainties …

A direction preserving discretization for computing phase-space densities

D Chappell, JJ Crofts, M Richter, G Tanner - SIAM Journal on Scientific …, 2021‏ - SIAM
Ray flow methods are an efficient tool to estimate vibro-acoustic or electromagnetic energy
transport in complex domains at high-frequencies. Here, a Petrov--Galerkin discretization of …

Efficient quadratures for high-dimensional Bayesian data assimilation

M Cheng, P Wang, DM Tartakovsky - Journal of Computational Physics, 2024‏ - Elsevier
Bayesian update is a common strategy used to combine (uncertain) model predictions and
(noisy) observational data. A computational bottleneck in this data assimilation technique is …

Model validation: A probabilistic formulation

A Halder, R Bhattacharya - 2011 50th IEEE Conference on …, 2011‏ - ieeexplore.ieee.org
This paper presents a probabilistic formulation of the model validation problem. The
proposed validation framework is simple, intuitive, and can account both deterministic and …

Hypersonic entry vehicle state estimation using nonlinearity-based adaptive cubature Kalman filters

T Sun, M **n - Acta Astronautica, 2017‏ - Elsevier
Guidance, navigation, and control of a hypersonic vehicle landing on the Mars rely on
precise state feedback information, which is obtained from state estimation. The high …

Further results on probabilistic model validation in Wasserstein metric

A Halder, R Bhattacharya - 2012 IEEE 51st IEEE Conference …, 2012‏ - ieeexplore.ieee.org
In a recent work [1], we have introduced a probabilistic formulation for the model validation
problem to provide a unifying framework for (in) validating nonlinear deterministic and …

Uncertainty quantification for stochastic nonlinear systems using Perron-Frobenius operator and Karhunen-Loève expansion

P Dutta, A Halder… - 2012 IEEE International …, 2012‏ - ieeexplore.ieee.org
In this paper, a methodology for propagation of uncertainty in stochastic nonlinear dynamical
systems is investigated. The process noise is approximated using Karhunen-Loève (KL) …