Implement SLS MPC for linear systems subject to polytopic model uncertainty and additive disturbances.

Open Optimal Control Library for Matlab. Trajectory Optimization and non-linear Model Predictive Control (MPC) toolbox.

Python code of the paper "Efficient Calibration of Embedded MPC" (2020 IFAC World Congress) by Marco Forgione, Dario Piga, and Alberto Bemporad

手写实现李航《统计学习方法》书中全部算法

Python code for implementing a set of basic robust model predictive control (RMPC) algorithms for linear systems.

Build your neural network easy and fast, 莫烦Python中文教学

Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

Simple examples for Event-triggered control for network controlled system

Code for the book

The repository is for safe reinforcement learning baselines.

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Benchmark for quadratic programming solvers available in Python

A sum-of-squares toolbox for stability analysis

Methods for computing the spectrum of chaotic systems

A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control

This is a Python realization for Milan Korda and Igor Mezic's paper Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control

A Python package to learn the Koopman operator.

All scripts and code related to the thesis, based on Koopman operators

Code for CDC2022 submission

This repo is for developing a Koopman operator based MPC for autonomous vehicles.

Neural Koopman Lyapunov Control

Develop a Koopman operator based MPC for controlling a quadrotor

Codebase for generating linear/bilinear/nonlinear Koopman model realizations from data and constructing MPC controllers.

All the code needed to learn models from data using Koopman operator approach.

a repository of the codes related with the paper published in the journal paper (check the readme file).

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

Koopman Reduced-Order Nonlinear Identification and Control