lyapunov-functions
There are 16 repositories under lyapunov-functions topic.
StanfordASL/neural-network-lyapunov
Synthesizing neural-network Lyapunov functions (and controllers) as stability certificate.
vdorobantu/lyapy
Library for simulation of nonlinear control systems, control design, and Lyapunov-based learning.
ZikangXiong/MFNLC
[IROS 22'] Model-free Neural Lyapunov Control
RylanSchaeffer/MIT2.152-Nonlinear-Control
MIT Spring 2020 Mechanical Engineering 2.152 Nonlinear Control (Professor Jean-Jacques Slotine)
maxhcohen/ControlBarrierFunctions.jl
Control barrier functions (CBFs) in Julia.
risherlock/Lyapunov
This repository contains lecture notes, solved problems, and simulation software on control systems in general.
risherlock/Spacecraft-Dynamics-and-Control
This repository contains lecture notes on the courses "(Advance) Spacecraft Dynamics and Control" by Hanspeter Schaub.
HaohanZou/CoNSAL
Official implementation of CoNSAL for analytical Lyapunov function discovery
mengyuest/nn_roa_planner
[L4DC2023] A neural network policy learning framework to stabilize hybrid systems for robots.
valvarezapa/LCD
Lyapunov Cycle Detector is a collection of algorithms destined to study the basins of attraction of rational maps (that is, the Fatou and Julia sets). In particular, the main focus of LCD is in the detection of attracting n-cycles of said rational map and in computing its basins.
abhijitmahalle/lateral_control_of_autonomous_vehicle
Implementation of research paper "Lateral Control of an Autonomous Vehicle." A controller is designed to control the lateral movement of autonomous vehicles on straight and curved roads using the principle of feedforward, backstepping, and preview point.
EthanJamesLew/PSU_STAT672
Notes, homework and project for PSU's STAT 672 Winter 2020
MIT-REALM/nn-hybrid-clf
[L4DC2023] A neural network policy learning framework to stabilize hybrid systems for robots.
zhang-zengjie/csur-coverage-control
Optimal coverage of multiple constant-speed unicycle robots
Grashopr-888/Serie-des-catastrophes-Visualizing-dynamic-parameters-in-Faraday-Wave-Patterns
Final Project for Leiden University Media Technology MSc. involving an advanced processing sketch that simulates the effect of catastrophe types on Faraday Wave pattern morphology during audiovisual playback. All code by Trent Eriksen and inspired by research from Amber van der Tuin
roscibely/lyapunov-based-nn-constriants-input
Lyapunov-based neural network control with input saturation constraints