Huang, Wei-HaoWei-HaoHuangNguyen, Phuc Thanh-ThienPhuc Thanh-ThienNguyenNguyen, Dai-DongDai-DongNguyenDoan, Hoang-PhuongHoang-PhuongDoanChuang, Ming-YangMing-YangChuangCHUNG-HSIEN KUO2025-06-302025-06-302025https://www.scopus.com/record/display.uri?eid=2-s2.0-105007421185&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/730331This article introduces a self-balancing bicycle utilizing a reaction wheel for stability control. To manage hardware complexity, a simplified test platform was first used for physical modeling and controller design with a linear-quadratic regulator (LQR), validating the concept. For the final implementation, the full-scale bicycle adopts full-state feedback. Although the LQR improved stability, its frequent motor speed adjustments led to high power consumption. To address this, a novel adaptive equilibrium point gradual algorithm (AEPGA) was developed to adapt to environmental changes, such as lateral imbalances. Performance tests on a real bicycle showed the AEPGA achieved maximum speed of 17 km/h on campus roads. In tests with a 2 kg lateral payload, AEPGA achieved a 67.456% reduction in power consumption compared to LQR over 22 s. For path tracking, a 3D LiDAR system was integrated. On a 77 m indoor corridor, the system reached an average speed of 1.39 km/h with a 0.153 m mean absolute error, while on a 190 m outdoor asphalt road, it reached 2.31 km/h with 0.283 m MAE. These results demonstrate the effectiveness of AEPGA in enhancing energy efficiency and adaptability, while maintaining reliable path tracking in varied environments.Adaptive equilibrium point gradual algorithm (AEPGA)linear-quadratic regulator (LQR)path trackingreaction wheelself-balancing bicycle[SDGs]SDG7[SDGs]SDG11journal article10.1109/TMECH.2025.3572225