Trajectory tracking control of wheeled mobile robots with skidding and time-varying delay

Mengqi Wang, Hua Chen, Yun Chen, Yuhan Cao, Linyuan Hou
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Abstract

This paper tackles the problem of trajectory tracking for wheeled mobile robots subject to time-varying input delay and bounded external disturbances. First, we establish a dynamic model for a wheeled mobile robot under sliding and skidding conditions, and determine the maximum allowable input delay that maintains system stability using Razumikhin-type stability analysis without prior knowledge of the variation in delay. The proposed adaptive robust controller combined with super-twisting sliding mode control is resilient to disturbances such as input delay, system uncertainty, and parameter variation. The proposed adaptive law enables real-time modification of switching gain based on tracking error without predefined knowledge of uncertainty bounds. Compared with traditional sliding mode control strategies, the super-twisting algorithm can eliminate chattering phenomenon while combined robust methods further reduce modeling uncertainties’ influence on system performance. Finally, we select an appropriate Lyapunov function to analyze and prove uniformly ultimately bounded of the closed-loop system. MATLAB simulation comparison results demonstrate that this approach achieves high tracking accuracy, faster response speed, and robustness.
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带滑行和时变延迟的轮式移动机器人的轨迹跟踪控制
本文探讨了受时变输入延迟和有界外部干扰影响的轮式移动机器人的轨迹跟踪问题。首先,我们建立了滑动和打滑条件下轮式移动机器人的动态模型,并在不预先知道延迟变化的情况下,利用拉祖米欣式稳定性分析确定了保持系统稳定性的最大允许输入延迟。所提出的自适应鲁棒控制器与超扭曲滑模控制相结合,能够抵御输入延迟、系统不确定性和参数变化等干扰。所提出的自适应法则可根据跟踪误差实时修改开关增益,而无需预先确定不确定性边界。与传统的滑模控制策略相比,超扭曲算法可以消除颤振现象,而组合鲁棒方法则进一步降低了建模不确定性对系统性能的影响。最后,我们选择了合适的 Lyapunov 函数来分析和证明闭环系统的均匀最终约束。MATLAB 仿真对比结果表明,该方法实现了较高的跟踪精度、较快的响应速度和鲁棒性。
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