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基于仿人操控的无人摩托自适应定车控制

王伯毅 邓飏 景飞龙 刘艳红 霍本岩 陈章 梁斌

自动化学报2026,Vol.52Issue(5):966-979,14.
自动化学报2026,Vol.52Issue(5):966-979,14.DOI:10.16383/j.aas.c250513

基于仿人操控的无人摩托自适应定车控制

Adaptive Track Stand Control for Unmanned Motorcycles Based on a Human-inspired Control Strategy

王伯毅 1邓飏 1景飞龙 1刘艳红 2霍本岩 2陈章 1梁斌1

作者信息

  • 1. 清华大学自动化系 北京 100084
  • 2. 郑州大学电气与信息工程学院 郑州 450001
  • 折叠

摘要

Abstract

When an unmanned motorcycle is at zero velocity,the centrifugal effect becomes ineffective,making bal-ance control extremely challenging and lacking a robust and efficient control mechanism.Inspired by track stand skills of human riders,this paper proposes a human-inspired control method for the stationary balance of un-manned motorcycles.The principle of track stand is elucidated and applied to stationary balance of rear-wheel-driv-en unmanned motorcycles.By deriving the dynamic equations and conducting rider experiments,the mechanism of track stand is analyzed from both model-based and data-driven perspectives,revealing the principles by which riders maintain balance and adapt to varying terrains.Building upon this insight,a robust equilibrium-adaptation track stand control method is proposed.The method estimates the disturbed equilibrium point by using a disturb-ance observer,and adopts nonlinear model predictive control to achieve balance control under disturbances.The proposed method is shown to ensure zero steady-state tracking error,and its effectiveness is validated through ex-periments.Experimental results show that the proposed method improves tolerable disturbances to about 3.1 times and 2.4 times those of the conventional model predictive control in track stand tasks on lateral and longitudinal slopes,respectively,and reduces tracking errors by one order of magnitude in rear wheel position tracking tasks.

关键词

无人摩托车/定车/仿生控制/抗扰控制

Key words

unmanned motorcycle/track stand/bio-inspired control/disturbance rejection control

引用本文复制引用

王伯毅,邓飏,景飞龙,刘艳红,霍本岩,陈章,梁斌..基于仿人操控的无人摩托自适应定车控制[J].自动化学报,2026,52(5):966-979,14.

基金项目

国家自然科学基金(62203252)资助 Supported by National Natural Science Foundation of China(62203252) (62203252)

自动化学报

0254-4156

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