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Optimal path planning of a cable-suspended robot with moving boundary using optimal feedback linearization approach

机译:使用最优反馈线性化方法的具有移动边界的电缆悬挂机器人的最佳路径规划

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In this paper, the optimal path of a cablesuspended robot between two boundaries is assessed subject to its maximum load, while the initial and target points are moving boundary. Considering the fact that the most important application of cable robots is load carrying between two boundaries, planning the optimal path in which the heaviest load can be carried is extremely applicable. A closed loop optimal path planning algorithm is proposed in this paper for non-linear dynamic of a cable robots based on optimal feedback linearization. This method not only produces the optimal path of the end-effector, but also is robust to external disturbances and parametric uncertainties as a result of its closed loop nature. Moreover, considering the fact that in many automation applications the target of load handling is a sort of moving boundary like conveyors, finding the optimal point of this boundary which produces the optimal path with the maximum dynamic load carrying capacity (DLCC) amongst the other points of the boundary is obviously a useful study. Therefore, an online solution, based on variational algorithm is proposed here to solve the moving boundary problem which is compatible with the presented closed loop optimal path planning. This method is developed for both the initial and final moving boundaries. Finally maximum DLCC is obtained using an iterative method to check the optimality of the proposed method. The efficiency of the proposed algorithm is verified at the end by the aid of some simulation scenarios performed on a spatial six DOFs cable robot with six cables. The motors' torque, motors' speed, and resultant DLCCs are calculated for both simple optimal path and moving boundary cases and comparison of the results proves the mentioned claims based on superiority of the proposed algorithm of moving boundary in saving the energy and increasing the DLCC. All simulation results are supported by conducting an experimental study on the cable robot of IUST (ICaSbot) for regulation movement of the end-effector with moving boundary.
机译:在本文中,悬吊式机器人在两个边界之间的最佳路径是根据其最大负载来评估的,而初始点和目标点是移动边界。考虑到电缆机械手最重要的应用是在两个边界之间进行负载承载,因此规划可承载最重负载的最佳路径非常适用。提出了一种基于最优反馈线性化的电缆机器人非线性动力学闭环最优路径规划算法。这种方法不仅可以产生末端执行器的最佳路径,而且由于其闭环特性,还可以抵抗外部干扰和参数不确定性。此外,考虑到以下事实:在许多自动化应用中,负载处理的目标是一种像运输机一样的移动边界,因此找到该边界的最佳点,该最佳点将在其他点中产生具有最大动态负荷能力(DLCC)的最佳路径边界显然是有用的研究。因此,本文提出了一种基于变分算法的在线解决方案,以解决与提出的闭环最优路径规划兼容的运动边界问题。此方法是针对初始和最终移动边界开发的。最后,使用迭代方法获得最大DLCC,以检查所提出方法的最优性。最后,借助在具有六根电缆的空间六自由度电缆机器人上执行的一些模拟方案,验证了所提出算法的效率。针对简单的最佳路径和运动边界情况,计算了电动机的转矩,电动机速度和所得的DLCC,结果的比较证明了所提出的权利要求基于所提出的运动边界算法在节省能量和增加DLCC方面的优势。 。所有仿真结果均通过在IUST的电缆机器人(ICaSbot)上进行实验研究来支持,该机器人通过运动边界调节末端执行器的运动。

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