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Higher order real-time approximations in optimal control of multibody-systems for industrial robots

机译:工业机器人多体系统最优控制中的高阶实时逼近

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摘要

The multibody system of an industrial robot leads to a mathematical model described by ordinary differential equations. Control functions have to be determined to calculate robot trajectories which are optimal due to a given performance index subject to additional constraints. In order to solve such optimal control problems, computationally expensive methods exist. These methods have no real-time capability, since perturbations during the motion of the robot require a recalculation of the optimal trajectory within a time frame much smaller than the operating-time of the robot. Hence, a robust numerical method based on the parametric sensitivity analysis of nonlinear optimization problems is suggested. Optimal control approximations of perturbed optimal solutions can be obtained in real-time by evaluating a first order Taylor expansion of the perturbed solution. Successive improvements to the constraints in the direction of the optimal perturbed solution lead to an admissible solution with a higher order approximation of the objective. The proposed numerical method is illustrated by the optimal control of an industrial robot with three degrees of freedom subject to deviations in the payload and initial values.
机译:工业机器人的多体系统导致了由常微分方程描述的数学模型。必须确定控制功能以计算由于给定的性能指标而受其他约束的影响而最佳的机器人轨迹。为了解决这种最优控制问题,存在计算上昂贵的方法。这些方法没有实时能力,因为在机器人运动过程中的扰动要求在比机器人操作时间小得多的时间范围内重新计算最佳轨迹。因此,提出了一种基于非线性优化问题的参数敏感性分析的鲁棒数值方法。通过评估被摄动解的一阶泰勒展开式,可以实时获得被摄动最优解的最优控制近似值。在最佳摄动解的方向上对约束的连续改进导致了目标的高阶近似的可接受解。所提出的数值方法通过具有三个自由度,受有效载荷和初始值偏差的工业机器人的最优控制来说明。

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