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<p>This paper presents a novel approach to adaptive robust trajectory tracking for nonholonomic wheeled mobile robots, utilizing a hybrid control law combining stable model predictive control (SMPC) for kinematic control and adaptive sliding mode control (ASMC) for dynamic control. The kinematic and dynamic characteristics of the robot, including longitudinal and lateral slip, are rigorously derived. To enhance computational efficiency, the kinematic portion is linearized using successive methods, followed by the application of a time-variant SMPC to determine wheel velocities, which serve as inputs to the adaptive dynamic controller. The ASMC component enhances robustness and accuracy in trajectory tracking. The proposed controller demonstrates effectiveness through zero steady-state error, rapid error convergence, reliable obstacle avoidance, and resilience to continuous disturbances and uncertainties. Experimental validation on a differential robot, tasked with tracking a circular path, confirms the controller’s precision and excellent tracking performance.</p>

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Hybrid Stable Adaptive Control Approach for Navigation of Nonholonomic Wheeled Mobile Robots on Slippery Surfaces With Obstacles

  • 期刊论文

  • 发表日期：

    2025年5月14日

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  • Moharam Habibnejad Korayem,
  • Fateme Namdarpour,
  • Naeim Yousefi Lademakhi

摘要

This paper presents a novel approach to adaptive robust trajectory tracking for nonholonomic wheeled mobile robots, utilizing a hybrid control law combining stable model predictive control (SMPC) for kinematic control and adaptive sliding mode control (ASMC) for dynamic control. The kinematic and dynamic characteristics of the robot, including longitudinal and lateral slip, are rigorously derived. To enhance computational efficiency, the kinematic portion is linearized using successive methods, followed by the application of a time-variant SMPC to determine wheel velocities, which serve as inputs to the adaptive dynamic controller. The ASMC component enhances robustness and accuracy in trajectory tracking. The proposed controller demonstrates effectiveness through zero steady-state error, rapid error convergence, reliable obstacle avoidance, and resilience to continuous disturbances and uncertainties. Experimental validation on a differential robot, tasked with tracking a circular path, confirms the controller’s precision and excellent tracking performance.