Advancements in Control Algorithms and Key Components for Self-Balancing Electric Unicycles: A Comprehensive Review

Self-balancing electric unicycles have gained significant attention in recent years as a novel and efficient means of personal transportation. This comprehensive review focuses on the recent developments in electric unicycles highlighting key components and sensors utilized in self-balancing electric unicycles which provide essential feedback for the control algorithms. The study explores the application of popular control algorithms such as PID (Proportional-Integral-Derivative), LQR (Linear Quadratic Regulator), ADRC (Active Disturbance Rejection Control), and adaptive control algorithms, etc. In the context of self-balancing electric unicycles. This study evaluates the benefits and challenges associated with these control algorithms, including their stability, responsiveness, robustness, and adaptability to different riding conditions. Moreover, the review delves into control algorithms specifically designed for gyroscopic control. The findings indicate that selecting key components based on design requirements is vital to constructing a unicycle that is simultaneously safe, stable, cost-effective, efficient, and environmentally friendly. LQR and ADRC algorithms are found highly effective in enhancing control performance in electric unicycles. When it comes to gyroscopic control, PID controllers, Kalman filters, Complementary filters, and adaptive control algorithms have proven to be effective and efficient in self-balancing electric unicycles.

I. Introduction

The advent of electric vehicles has brought about a revolution in personal transportation. While electric cars and bicycles have become popular over the years, another innovative form of personal transportation that has recently gained traction is the electric unicycle. An electric unicycle is a single-wheeled self-balancing vehicle that has captured the imagination of many people due to its unique design and functionality [1].