Aleksandar Haber's repositories
Model-Predictive-Control-Implementation-in-Python-1
Here, we post the codes that implement the Model Predictive Controller (MPC) for linear systems.
Model-Predictive-Control-for-Linear-Systems-in-Cpp-by-Using-Eigen-Library
This repository contains C++ files that explain how to implement the Model Predictive Control (MPC) algorithm for linear systems in C++ by using the Eigen C++ matrix library.
Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks
This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.
Linear-Quadratic-Regulator-Optimal-Control-in-Cpp-From-Scratch-by-Using-Newton-Method
We implemented a solution of the Linear Quadratic Regulator (LQR) Optimal Control problem in C++. We use the Newton method to solve the Riccati equation and to compute the solution.
Machine-Learning-and-System-Identification-for-Adaptive-Optics
This project deals with system identification and machine learning of large-scale deformable mirrors used in adaptive optics. I have submitted two papers that deal with this important problem. The approaches can be generalized two other problems of estimating large-scale system with the dynamics described by partial differential equations.
Deep-Q-Learning-Network-from-Scratch-in-Python-TensorFlow-and-OpenAI-Gym
These code files implement the deep Q learning network algorithm from scratch by using Python, TensorFlow, and OpenAI Gym. The codes are tested in the OpenAI Gym Cart Pole (v1) environment.
Save-and-Load-Eigen-Cpp-Matrices-Arrays-to-and-from-CSV-files
The functions provided in this C++ source files are used to save and load Eigen C++ matrices/arrays to and from CSV values.
Mobile-Robot-Dead-Reckoning-and-Visualization-of-Motion-in-RViz
In this repository, we post Robot Operating System (ROS) and Python code that implement real-time robot motion tracking using dead reckoning and visualization in real-time in RViz.
Demonstration-of-Cart-Pole-OpenAI-Gym-Reinforcement-Learning-Environment-in-Python-
This code file demonstrates how to use the Cart Pole OpenAI Gym (Gymnasium) environment in Python.
Simulation-and-Animation-of-Cart-Pole-State-Space-Model-in-Python-and-Pygame
In this GitHub repository we posted Python scripts that are used to automatically derive a symbolic state-space model of a cart
Disciplined-Kalman-Filter-Implementation-in-Python
This code implements the Kalman filter in Python by using an object oriented approach.
Multi-Armed-Bandit-Problem-and-Epsilon-Greedy-Action-Value-Method-in-Python
This GitHub repository contains Python implementation of the epsilon-greedy action value method for solving multi-armed bandit problem.
Phase-portraits-of-dynamical-systems-and-state-space-models-in-Python
In this Python dynamical system tutorial, we explain how to construct phase portraits of dynamical systems and state-space models. The posted code will construct a phase portrait and a state-space trajectory of a dynamical system. The webpage tutorial accompanying these codes is given here: https://aleksandarhaber.com/phase-portraits-of-state-space
Q-Learning-Algorithm-in-Python-with-Cart-Pole-OpenAI-Gym--Gymnasium-Environment
In this repository, we post the implementation of the Q-Learning (Reinforcement) learning algorithm in Python. The codes are tested in the Cart Pole OpenAI Gym (Gymnasium) environment.
ROS_modeling_using_xacro_and_urdf
These repository contains xacro/urdf and launch files necessary to model a robot.
Bagging-Classifier-in-Python
In this repository, we posted the codes that demonstrate how to implement the Bagging classifier in the Scikit-learn library and Python.
Eigen-Cpp-Matrix-Library-Demonstration
This repository contains code files that demonstrate how to use the Eigen C++ Matrix library for performing the basic matrix operations, computing eigenvalues, solving linear systems, and computing matrix decompositions.
SARSA-Temporal-Difference-Learning-in-Python
These code files implement the on-policy SARSA (State-Action-Reward-State-Action) reinforcement learning algorithm in Python.