Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

控制算法，状态、输出反馈控制。ADRC自抗扰控制，抗积分饱和PID控制，增量式PID控制，模糊FuzzyPID控制，线性二次型调节器LQR控制，线性二次型积分器LQI控制，迭代iLQR控制，模型预测MPC控制，AI智能控制，启发算法控制，强化学习SAC、PPO控制，无人机、机器人、小车轨迹跟踪控制

GPU-friendly, auto-differentiable LQR solver with JAX.

HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

Differential Dynamic Programming controller operating in OpenAI Gym environment.

A toolbox for trajectory optimization of dynamical systems

This repository contains CartPole simulator with its GUI, implemented controller (LQR) and generator of random desired position trace. It also contains files to train and test RNN predicting future states of a CartPole.

LQR controller for quadrotors

This project aims to design a LQR controller to control a car following a trajectory as accurate and fast as possible

Various Control Barrier Functions realized on cartpole.

An implementation of model-predictive control algorithms using TensorFlow 2

Contains simple MPC implementation with neural network learned dynamics.

This research contains formulation and implementation of LQR (Linear Quadratic Regulator) Guidance for ship based net recovery of fixed wing UAVs

Differentiable MPC in Chainer, developed as part of PFN summer internship 2019.

Simulates the dynamics of a Reaction Wheel Inverted Pendulum with python.

Implicit Differentiable Optimal Control (IDOC) with JAX

Control inverted pendulum by LQR in OpenAI Gym

A framework for implementing path tracking algorithms at ROS and Pyhton. Including implementations of three methods: Pure Pursuit, MPC, and LQR.

Developing a ROS-Package of a linear inverted pendulum with N-Links along with a controller and create Tutorials for the same.

Model-free policy gradient algorithm for LQR