2,412 research outputs found
Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems
Development of robust dynamical systems and networks such as autonomous
aircraft systems capable of accomplishing complex missions faces challenges due
to the dynamically evolving uncertainties coming from model uncertainties,
necessity to operate in a hostile cluttered urban environment, and the
distributed and dynamic nature of the communication and computation resources.
Model-based robust design is difficult because of the complexity of the hybrid
dynamic models including continuous vehicle dynamics, the discrete models of
computations and communications, and the size of the problem. We will overview
recent advances in methodology and tools to model, analyze, and design robust
autonomous aerospace systems operating in uncertain environment, with stress on
efficient uncertainty quantification and robust design using the case studies
of the mission including model-based target tracking and search, and trajectory
planning in uncertain urban environment. To show that the methodology is
generally applicable to uncertain dynamical systems, we will also show examples
of application of the new methods to efficient uncertainty quantification of
energy usage in buildings, and stability assessment of interconnected power
networks
Data-driven model reduction and transfer operator approximation
In this review paper, we will present different data-driven dimension
reduction techniques for dynamical systems that are based on transfer operator
theory as well as methods to approximate transfer operators and their
eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out
similarities and differences between methods developed independently by the
dynamical systems, fluid dynamics, and molecular dynamics communities such as
time-lagged independent component analysis (TICA), dynamic mode decomposition
(DMD), and their respective generalizations. As a result, extensions and best
practices developed for one particular method can be carried over to other
related methods
Geometric Numerical Integration
The subject of this workshop was numerical methods that preserve geometric properties of the flow of an ordinary or partial differential equation. This was complemented by the question as to how structure preservation affects the long-time behaviour of numerical methods
Computational intelligence approaches to robotics, automation, and control [Volume guest editors]
No abstract available
Approximation of slow and fast dynamics in multiscale dynamical systems by the linearized Relaxation Redistribution Method
In this paper, we introduce a fictitious dynamics for describing the only
fast relaxation of a stiff ordinary differential equation (ODE) system towards
a stable low-dimensional invariant manifold in the phase-space (slow invariant
manifold - SIM). As a result, the demanding problem of constructing SIM of any
dimensions is recast into the remarkably simpler task of solving a properly
devised ODE system by stiff numerical schemes available in the literature. In
the same spirit, a set of equations is elaborated for local construction of the
fast subspace, and possible initialization procedures for the above equations
are discussed. The implementation to a detailed mechanism for combustion of
hydrogen and air has been carried out, while a model with the exact
Chapman-Enskog solution of the invariance equation is utilized as a benchmark.Comment: accepted in J. Comp. Phy
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