lqg-controller

A Control Systems Toolbox for Julia

Master's Thesis Project: Design, Development, Modelling and Simulating of a Y6 Multi-Rotor UAV, Imlementing Control Schemes such as Proportional Integral Derivative Control, Linear Quadratic Gaussian Control and Model Predictive Control on a BeagleBone Blue

Self-balancing robot analysis and LQG optimal controller design with MATLAB Simulink and Simscape Multibody

LQR and LQG control for gantry crane with 2 connected masses

modeling system dynamics incl. actuators and continuous / discrete controller designs in MATLAB Simulink integrated computer vision using segmentation

End-to-end AO pipeline: SH-WFS centroiding (127x C speedup) → CNN/MMSE reconstruction (Strehl 0.9987) → LQG closed-loop control → SLODAR turbulence profiling | BAH 2026 Challenge #9

Linear Quadratic Regulator and Linear Quadratic Gaussian Controller Design for a crane system.

Welcome to the Optimal Control course repository at K.N. Toosi University of Technology! This repository serves as a hub for sharing course materials and homework assignments related to the fascinating field of optimal control.

LQR-LQG-Controller Design

Advanced control system project, based on simulation with LQR, LQG, and Kalman Filter methods

Inverted double-pendulum state observer feedback control (SOFC) simulation and verification

LQR and LQG control for gantry crane with 2 connected masses

LQG controller to control the dual pendulum cart

ENPM 667- Controls for Robotics Systems: Final Project

Modeling of double pendulum suspended on a cart system, and designing LQR controllers and LQG controllers to control state variables like cart position, pendulum angular displacement, velocity

Control system simulation with LQR, Pole Placement, and LQG methods

LQR, LQG Controller Implementation and Analysis for a two load Crane Problem (Inverted Pendulum)

EN: Linearization and LQR+LQG control of reverse pendulum on cart system. ---- IT: Linearizzazione e controllo LQR+LQG del sistema pendolo inverso su carrello

This project involves the development of a two-load crane control system, implemented as part of the ENPM667 Robotics course. The main objective was to enhance the crane's dynamic response and stability using advanced control algorithms.

This repository includes two projects completed as part of the coursework. The first project involves replicating a research paper comparing controllers for a differential drive robot. The second project focuses on implementing LQR and LQG controllers for a crane system using MATLAB. Both projects demonstrate the knowledge acquired during the cours