Comparison of Different Control Theories on a Two Wheeled Self Balancing Robot

TL;DR

This paper compares PID, LQR, and Fuzzy logic controllers on a simulated two-wheeled self-balancing robot using ROS and Gazebo, analyzing their performance and modeling approaches.

Contribution

It provides a detailed comparison of three control theories applied to a self-balancing robot in simulation, including modeling, implementation, and performance analysis.

Findings

LQR outperforms PID and Fuzzy in stability and response time.

Fuzzy logic offers robustness to disturbances.

PID is simpler but less effective in complex scenarios.

Abstract

. This paper is aimed to discuss and compare three of the most famous Control Theories on a Two wheeled Self Balancing Robot Simulation using Robot Operating System (ROS) and Gazebo. Two Wheeled Self Balancing Robots are one of the most fascinating applications of Inverted Pendulum System. In this paper, PID, LQR and Fuzzy logic controllers are discussed . Also,0 the modeling and algorithms of the robot simulation is discussed. The primary objectives of this paper is to discuss about the building of a robot model in ROS and Gazebo , experimenting different control theories on them, documenting the whole process with the analysis of the robot and comparison of different control theories on the system.