通过仿骑车者姿态实现单轨两轮机器人静止平衡控制
Equilibrium Adaptation-Based Control for Track Stand of Single-Track Two-Wheeled Robots
- 借鉴骑车人动作，仅用转向和后轮驱动实现平衡
- 可自适应慢变干扰，跟踪误差降几个数量级
- 适合需要高精度静止平衡的移动机器人研究
单轨两轮（STTW）机器人在静止平衡控制方面面临挑战，主要源于缺乏优雅的平衡机制，以及有限吸引域与外部扰动之间的矛盾。为解决平衡机制缺失问题，本文借鉴骑车人经验，采用仅依赖转向和后轮驱动的轨道驻停（track stand）操作。为在匹配与非匹配扰动下实现精确跟踪，提出基于平衡点自适应控制（EABC）方案，可无缝集成标准扰动观测器与控制器。该方案利用扰动平衡点估计器，实现对慢变扰动的自适应，统一处理匹配与非匹配扰动，确保零稳态跟踪误差。将EABC与非线性模型预测控制（MPC）结合，应用于STTW机器人的轨道驻停任务，并通过两个实验场景验证有效性。结果表明，本方法显著提升跟踪精度，误差降低数个数量级。
原文摘要 · Abstract (English)
Stationary balance control is challenging for single-track two-wheeled (STTW) robots due to the lack of elegant balancing mechanisms and the conflict between the limited attraction domain and external disturbances. To address the absence of balancing mechanisms, we draw inspiration from cyclists and leverage the track stand maneuver, which relies solely on steering and rear-wheel actuation. To achieve accurate tracking in the presence of matched and mismatched disturbances, we propose an equilibrium adaptation-based control (EABC) scheme that can be seamlessly integrated with standard disturbance observers and controllers. This scheme enables adaptation to slow-varying disturbances by utilizing a disturbed equilibrium estimator, effectively handling both matched and mismatched disturbances in a unified manner while ensuring accurate tracking with zero steady-state error. We integrate the EABC scheme with nonlinear model predictive control (MPC) for the track stand of STTW robots and validate its effectiveness through two experimental scenarios. Our method demonstrates significant improvements in tracking accuracy, reducing errors by several orders of magnitude.
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