An experimental study on the PID and Fuzzy-PID controllers on a designed two-wheeled self-balancing autonomous robot

This paper presents a dynamic model and control strategies for a two-wheeled self-balancing robot. The dynamic model of the under study two-wheeled self-balancing robot is calculated based on Newtonian method and the control strategies is designed based on the calculated dynamic model which is constructed for this paper. The parameters of the proposed robot which are used for controlling the proposed robot are tilt angle and displacement of the proposed robot. Based on the system zeroes and poles location which are calculated based on transfer functions of the under study robot, proportional derivative and proportional integral derivative controllers are designed. The controllers parameters are tuned with the Genetic algorithm. Fuzzy logics are used to improve the balance ability especially under external forces. The experimental results of implementing the proportional derivative controller represented that a slight vibration is appeared on the body of the proposed robot and it fell down after few seconds. The proportional integral derivative controller improved the stability of the proposed robot but the robot fell down when an external force is applied on the body of it. After implementing the designed Fuzzy-PID controller on the under study two-wheeled self-balancing robot, the stability of the under study two wheel self-balancing robot under external forces is improved impressively.

I. Introduction

In recent decades, many researches have been conducted on urban transport non-pollutant vehicles. Due to the proposed requirements, various kind of non-pollutant vehicles are designed and constructed. Self-balancing robots are kind of robot which can be provided the proposed purposes. The features of self-balancing robots which makes them attractive for users can be regarded as: 1

No need of fossil fuels;

2

High ease of use and great maneuverability because of independent control of two wheels;

3

Lower cost of energy than fossil fuels;