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刚柔复合驱动并联式拣矸机器人动力学与鲁棒模型预测控制

On the dynamics and robust model predictive control of a rigid-flexible hybrid-driven parallel gangue sorting robot

  • 摘要: 矸石分拣可以提升煤炭品质、降低运输成本、减少环境污染,实现煤炭资源的高效清洁利用与矿山可持续发展。传统煤矸石人工分拣存在劳动强度大、效率低的问题,提出刚柔复合驱动并联式拣矸机器人构型方案。但是由于拣矸置矸过程所导致的动态冲击和动力学参数的不确定,以及外界干扰等因素,势必会影响拣矸机器人末端抓斗的跟踪精度和稳定性,甚至导致拣矸任务无法完成。鉴于此,开展了刚柔复合驱动并联式拣矸机器人动力学与鲁棒模型预测控制研究。首先,提出了刚柔复合驱动并联式拣矸机器人系统方案,分析了机器人末端抓斗的自由度,并采用矢量封闭原理建立了拣矸机器人的运动学模型。其次,考虑机器人模型参数摄动和拣矸置矸过程的外部扰动,基于牛顿−欧拉方程建立了刚柔复合驱动并联式拣矸机器人的动力学模型。再次,提出了融合张力约束的鲁棒模型预测控制方法,实时优化柔索−推杆驱动力协同分配,动态抵消抓取矸石抓取与置放过程的冲击与外部扰动,实现拣矸机器人末端抓斗高精度轨迹跟踪控制。最后,采用空间螺旋轨迹和4段式分拣轨迹(启动段—准备段—抓矸段—置矸段)对刚柔复合驱动并联式拣矸机器人鲁棒模型预测控制系统进行了仿真分析,结果表明末端抓斗轨迹最大偏移量仅3.7×10−3 m,姿态角误差稳定于3.2×10−3 rad,且柔索张力始终满足驱动力约束条件,验证了控制策略对复杂工况下拣矸作业的有效性。

     

    Abstract: The separation of coal and gangue plays a pivotal role in enhancing coal quality, reducing transportation costs, and mitigating environmental pollution, thereby facilitating the efficient and clean utilization of coal resources and promoting sustainable mine development. To address the challenges of high labor intensity and low efficiency inherent in traditional manual gangue sorting, a rigid-flexible hybrid-driven parallel gangue sorting robot consisting of a rigid drive rod and four cables is proposed. However, the dynamic impacts arising from the pick-and-place operation of the gangues, uncertainties in dynamic parameters, and external disturbances inevitably have an important influence on the tracking accuracy and stability of the gripper of the robot, potentially leading to the failure of the pick-and-place operation of the target gangues. As a result, the dynamics and robust model predictive control for the proposed rigid-flexible hybrid-driven parallel gangue sorting robot are investigated. First, a systematic scheme for the proposed rigid-flexible hybrid-driven parallel gangue sorting robot is presented, including an analysis of the degrees of freedom and the establishment of its kinematic model. Second, taking into account the parameter perturbations in the robot’s model and external disturbances during the pick-and-place operation of the target gangues, the dynamic model of the robot is developed with the Newton-Euler method. Third, a robust model predictive control method incorporating tension constraints is proposed for the presented rigid-flexible hybrid-driven parallel gangue sorting robot, which optimizes the real-time collaborative allocation of the driving forces of the four cables and the rigid drive rod. This method dynamically counteracts impacts and external disturbances during of the pick-and-place of the gangues, enabling high-precision trajectory tracking control for the gripper of the robot. Finally, some simulations are performed for the proposed rigid-flexible hybrid-driven parallel gangue sorting robot using a spatial helical trajectory and a four-segment sorting trajectory. And the results demonstrate that the maximum trajectory deviation of the gripper is limited to 3.7×10−3 m, the attitude angle error stabilizes at 3.2×10−3 rad, and cable tensions consistently satisfy the driving force constraints. These findings verify the effectiveness of the proposed control strategy in reliable pick-and-place operation of the gangues under complex operational conditions.

     

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