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Evaluation of Direct Collocation Optimal Control Problem Formulations for Solving the Muscle Redundancy Problem

机译:解决肌肉冗余问题的直接配置最优控制问题公式的评估

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摘要

Estimation of muscle forces during motion involves solving an indeterminate problem (more unknown muscle forces than joint moment constraints), frequently via optimization methods. When the dynamics of muscle activation and contraction are modeled for consistency with muscle physiology, the resulting optimization problem is dynamic and challenging to solve. This study sought to identify a robust and computationally efficient formulation for solving these dynamic optimization problems using direct collocation optimal control methods. Four problem formulations were investigated for walking based on both a two and three dimensional model. Formulations differed in the use of either an explicit or implicit representation of contraction dynamics with either muscle length or tendon force as a state variable. The implicit representations introduced additional controls defined as the time derivatives of the states, allowing the nonlinear equations describing contraction dynamics to be imposed as algebraic path constraints, simplifying their evaluation. Problem formulation affected computational speed and robustness to the initial guess. The formulation that used explicit contraction dynamics with muscle length as a state failed to converge in most cases. In contrast, the two formulations that used implicit contraction dynamics converged to an optimal solution in all cases for all initial guesses, with tendon force as a state generally being the fastest. Future work should focus on comparing the present approach to other approaches for computing muscle forces. The present approach lacks some of the major limitations of established methods such as static optimization and computed muscle control while remaining computationally efficient.Electronic Supplementary MaterialThe online version of this article (doi:10.1007/s10439-016-1591-9 contains supplementary material, which is available to authorized users.
机译:运动过程中的肌肉力量估算通常需要通过优化方法来解决不确定的问题(比关节力矩约束更多的未知肌肉力量)。当对肌肉激活和收缩的动力学进行建模以与肌肉生理学保持一致时,所产生的优化问题是动态的,并且难以解决。这项研究试图确定一种鲁棒且计算效率高的公式,以使用直接搭配的最佳控制方法来解决这些动态优化问题。基于二维和三维模型,研究了四个步行问题公式。在使用肌肉长度或肌腱力作为状态变量的收缩动力学的显式或隐式表示中,配方的使用有所不同。隐式表示法引入了定义为状态时间导数的其他控件,从而允许将描述收缩动力学的非线性方程式作为代数路径约束施加,从而简化了评估过程。问题表述影响了计算速度和初始猜测的鲁棒性。在大多数情况下,使用以肌肉长度为状态的显式收缩动力学的配方未能收敛。相反,在所有情况下,对于所有最初的猜测,使用隐式收缩动力学的两种公式在所有情况下都收敛于最优解,其中腱力通常是最快的状态。未来的工作应集中在将本方法与其他用于计算肌肉力量的方法进行比较。本方法缺乏已建立方法的一些主要限制,例如静态优化和计算机控制肌肉,同时仍保持计算效率。电子补充材料本文的在线版本(doi:10.1007 / s10439-016-1591-9-9)包含补充材料,其中适用于授权用户。

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