基于降阶ESO的全方位移动机器人滑模控制

Sliding Mode Control of Omnidirectional Mobile Robots Based on Reduced-order ESO

  • 摘要: 全方位移动机器人(OMR)在复杂环境中的轨迹跟踪精度易受系统不确定性和外部扰动的影响。为提高MY-3全方位移动机器人的轨迹跟踪性能,提出了一种基于降阶扩张状态观测器(ROESO)的滑模控制(SMC)方法。首先,建立MY-3机器人的数学模型,并将系统不确定性、非线性项及外部扰动统一建模为“总扰动”,利用ROESO对其进行实时估算与补偿,以减少其对系统的影响,同时避免惯性矩阵的逆运算。在此基础上,设计滑模控制律并与ROESO相结合,以增强系统的鲁棒性并抑制滑模控制中的抖振问题。最后通过仿真和实物实验验证了所提方法在负载变化下的鲁棒性。实验结果表明,所提方法在负载变化下具有良好的鲁棒性,能够显著减少轨迹跟踪误差,提高系统的跟踪精度,并增强对外部扰动的适应能力。同时,控制信号变得更加平稳,验证了ROESO在扰动补偿方面的有效性。

     

    Abstract: The trajectory tracking accuracy of omnidirectional mobile robots (OMR) is easily affected by system uncertainties and external disturbances in complex environments. To improve the trajectory tracking performance of the MY-3 omnidirectional mobile robot, we propose a sliding mode control (SMC) method based on reduced-order extended state observer (ROESO). Firstly, we establish a mathematical model of the MY-3 robot, and unify the system uncertainties, nonlinear terms, and external disturbances as “total disturbance”, which is real-time estimated and compensated by the ROESO to reduce its impact on the system, while avoiding the inversion of the inertia matrix. Based on this, we design a sliding mode control law, and combine it with the ROESO to enhance the system's robustness and suppress the chattering problem in sliding mode control. Finally, simulations and physical experiments validate the robustness of the proposed method under load variations. The results show that the proposed method has good robustness under load variations, significantly reduces the trajectory tracking error, improves the system’s tracking accuracy, and enhances its adaptability to external disturbances. Meanwhile, the control signal becomes smoother, verifying the effectiveness of the ROESO in disturbance compensation.

     

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