协调扭矩控制,增强独立驱动移动机器人的转向和稳定性

Liang Wang, Shoukun Wang, Junzheng Wang
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引用次数: 0

摘要

目的采用独立车轮控制的移动机器人在转向精度、运动稳定性和鲁棒性方面面临着各种车轮和转向系统类型的挑战。本文旨在提出一种协调扭矩分配控制方法,利用主动转向产生的纵向力矩补偿跟踪偏差。设计/方法/途径基于两自由度机器人模型,使用自适应鲁棒控制器计算总纵向力矩,同时根据自主转向与纵向力矩之间的差值调节机器人致动器。我们开发了一种自适应鲁棒控制方案,以精确、稳定地生成所需的总力矩值。研究结果与自主转向阿克曼速度控制和平均力矩方法进行的比较评估验证了所提出的控制策略的优越性能,表明在不同的驾驶条件下,机器人的跟踪精度和稳定性都有所提高。研究局限/意义在设计自适应算法时,使用自由度更高的模型可以提高精度。此外,还可以探索在力矩分布中加入额外的目标函数,以增强适应性,尤其是在极端环境中。原创性/价值通过将该方法与路径跟踪算法相结合,可以优化和提高机器人的结构路径跟踪能力以及在各种困难地形中的导航能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coordinated torque control for enhanced steering and stability of independently driven mobile robots

Purpose

Mobile robots with independent wheel control face challenges in steering precision, motion stability and robustness across various wheel and steering system types. This paper aims to propose a coordinated torque distribution control approach that compensates for tracking deviations using the longitudinal moment generated by active steering.

Design/methodology/approach

Building upon a two-degree-of-freedom robot model, an adaptive robust controller is used to compute the total longitudinal moment, while the robot actuator is regulated based on the difference between autonomous steering and the longitudinal moment. An adaptive robust control scheme is developed to achieve accurate and stable generation of the desired total moment value. Furthermore, quadratic programming is used for torque allocation, optimizing maneuverability and tracking precision by considering the robot’s dynamic model, tire load rate and maximum motor torque output.

Findings

Comparative evaluations with autonomous steering Ackermann speed control and the average torque method validate the superior performance of the proposed control strategy, demonstrating improved tracking accuracy and robot stability under diverse driving conditions.

Research limitations/implications

When designing adaptive algorithms, using models with higher degrees of freedom can enhance accuracy. Furthermore, incorporating additional objective functions in moment distribution can be explored to enhance adaptability, particularly in extreme environments.

Originality/value

By combining this method with the path-tracking algorithm, the robot’s structural path-tracking capabilities and ability to navigate a variety of difficult terrains can be optimized and improved.

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