summary of research work about successive linearization
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Updated
Sep 27, 2024 - MATLAB
summary of research work about successive linearization
DuckDB Extension Linearization/Delinearization, Z-Order, Hilbert and Morton Curves
Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event
Interface between ControlSystems and ModelingToolkit
Repository to design and implement LQR control on an AUV by ECA-Group
Repository for AUV Control Optimisation using LQR Project with ECA Group
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python…
This is a library with different sub-libraries to provide basic functions, which can be used in data and signal processing and to compare measurement results against simulation.
Files related to my Summer of Science Report on Nonlinear Dynamics
A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python
a quadratic linealization example, using python-mip library and coinOR solver
This code studies a linearized PF model through a data-driven approach.
Controllers designed to the 5MW NREL wind turbine using Simulink and Fast V8
Search for linearizing sets to solve inversion problem
The lightweight library to display Icons SVG
Functions and guide to use automatic differentiation for material modelling in deal.II on the element and QP level
A website I created giving a brief overview of mathematical optimization techniques. These techniques can be useful in understanding the intuition behind machine learning algorithms.
Fault Tolerance Project
Feedback linearization for quadrotors
Interpreting neural networks by reducing nonlinearities during training
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