Nonlinear dynamical systems simulations using Julia with Matlab interoperability
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Updated
Mar 17, 2022 - Jupyter Notebook
Nonlinear dynamical systems simulations using Julia with Matlab interoperability
Fortran90 examples of Dynamic Systems
Evaluate the Lyapunov Spectrum of a dynamical system described by ODEs (in Python)
A cutting-plane method to synthesize Lyapunov functions for neural network uncertain systems.
This my master's degree graduation thesis, it's about DC motor speed control using the sliding mode method, the motor it's controlled based on three models which are cascade and reduced, and complete model. the method has proved that it's robust against dc motor parameters changing and able to track a reference speed.
A Python package to simulate and measure chaotic dynamical systems.
LQG controller to control the dual pendulum cart
LATEX report of my literature study into stable variable impedance learning.
Codigo Fortran que implementa el metodo de Benettin para realizar el calculo de los exponentes de Lyapunov y posteriormente seleccionando un parámetrodell modelo realizar un espectro de los Exponentes de Lyapunov.
Compute Lyapunov exponents and Covariant-Lyapunov-Vectors of an RNN update trajectory
Calculating Lyapunov indicators with multiprocessing in Python
Fractal images with Python
P4 (Polynomial Planar Phase Portraits) software for phase portrait computation and representation in the plane or other projections such as the Poincaré Sphere.
RAILS: Residual Approximation-based Iterative Lyapunov Solver
command line tool that generates ppm images to visualize dynamic system functions
PyTorch implementation of "Learning Stable Deep Dynamics Models" (https://papers.nips.cc/paper/9292-learning-stable-deep-dynamics-models), with extensions to controlled dynamical systems.
Python package to compute Lyapunov exponents, covariant Lyapunov vectors (CLV) and adjoints of a dynamical systems.
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