LQR and LQG control for gantry crane with 2 connected masses
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Updated
Feb 27, 2023 - MATLAB
LQR and LQG control for gantry crane with 2 connected masses
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.
Design of LQR and LQG Controllers for two inverted pendulums on a moving cart
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
ENPM 667- Controls for Robotics Systems: Final Project
Helicopter lab at NTNU, using LQ-control in order control a miniture helicopter
Control system simulation with LQR, Pole Placement, and LQG methods
ENPM667 (Control of Robotic Systems) - Final Project
Inverted double-pendulum state observer feedback control (SOFC) simulation and verification
LQR, LQG Controller Implementation and Analysis for a two load Crane Problem (Inverted Pendulum)
LQG controller to control the dual pendulum cart
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
LQR-LQG-Controller Design
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
Advanced control system project, based on simulation with LQR, LQG, and Kalman Filter methods
Linear Quadratic Regulator and Linear Quadratic Gaussian Controller Design for a crane system.
Design and Simulation of LQR and LQG Controller for Crane System
python lib for linear quadratic control
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