基于U模型双层复合抗扰的全向车辆轨迹跟踪
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作者单位:

1.武汉科技大学人工智能与自动化学院;2.英国西英格兰大学工程学院(School of Engineering, University of the West of England, Bristol)

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TP273

基金项目:

国家自然科学基金项目(62073250,62173262)


Trajectory tracking of omnidirectional vehicles based on U-model dual layer composite anti-disturbance control
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National Natural Science Foundation of China (Grant Nos. 62073250 and 62173262)

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    摘要:

    针对麦克纳姆轮全向车辆在名义反演失配、轮端扰动、车体层外扰及参考速度变化条件下轨迹跟踪性能退化的问题,提出一种基于U模型的双层复合抗扰轨迹跟踪方法。首先,在车体层构造参考整形外环,根据位姿误差和速度跟踪误差对期望车体速度进行前置修正,并分配得到轮端参考量;其次,在轮端层构造以U模型动态逆为名义控制通道的控制内环,实现名义闭环塑形;进一步,设计残差型Super-Twisting二阶滑模补偿律,并结合轮端扰动观测前馈补偿,在线削弱名义反演失配、建模误差及综合扰动影响。基于MATLAB/Simulink平台开展基准跟踪、直线—曲线组合轨迹、复合扰动、分段变速及变速+限幅工况对比仿真。结果表明,所提方法在复杂工况下具有较好的轨迹跟踪精度、抗扰能力与精度保持性能。

    Abstract:

    To address the degradation of trajectory-tracking performance of Mecanum-wheeled omnidirectional vehicles caused by nominal inversion mismatch, wheel-end disturbances, body-level disturbances, and variations in reference speed, a dual-layer composite anti-disturbance trajectory-tracking method based on the U-model is proposed. First, a reference-shaping outer loop is constructed at the body level, where the desired body velocity is pre-corrected according to the pose error and velocity-tracking error and then allocated to wheel-end reference signals. Second, a wheel-end control inner loop with U-model-based dynamic inversion as the nominal control channel is constructed to realize nominal closed-loop shaping. Furthermore, a residual Super-Twisting second-order sliding-mode compensation law is designed and integrated with wheel-end disturbance-observer-based feedforward compensation to attenuate nominal inversion mismatch, modeling errors, and composite disturbances online. Comparative simulations under benchmark tracking, line--curve combined-trajectory tracking, composite disturbances, piecewise variable-speed conditions, and variable-speed conditions with input saturation are carried out on the MATLAB/Simulink platform. The results show that the proposed method achieves satisfactory tracking accuracy, disturbance rejection, and accuracy-retention performance under complex operating conditions.

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  • 收稿日期:2026-04-21
  • 最后修改日期:2026-08-27
  • 录用日期:2026-08-27
  • 在线发布日期: 2026-09-28
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