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Biomechanical optimal control of human arm motion

机译:人体手臂运动的生物力学最优控制

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摘要

As both ordinary and well-trained human motion is mostly planned and controlled unconsciously by the central nervous system (CNS), human control mechanisms remain relatively obscure. Despite, they are an interesting topic, for example, with regard to improve protheses or athletic motion. To learn and understand more about the control of human motion, we use rigid multibody systems to represent bones and joints and formulate an optimal control problem (OCP) with the goal to minimise a physiologically motivated cost function, while the equations of motion and further nonlinear constraints have to be fulfilled. The investigated biomechanical movements are induced either via joint torques or via Hill-type muscle forces. We compare several cost functions known from literature to another one concerning the impact on the joints by involving the constraint forces. A direct transcription method called DMOCC (discrete mechanics and optimal control for constraint systems) is used to solve the OCP, whereby we benefit from its structure preserving formulation, as the resulting optimal discrete trajectories are symplectic-momentum preserving.
机译:由于普通的和训练有素的人体运动大多是由中枢神经系统(CNS)无意识地计划和控制的,因此人体控制机制仍然相对模糊。尽管如此,它们还是一个有趣的话题,例如,在改善假肢或运动方面。为了学习和理解有关人体运动控制的更多信息,我们使用刚性多体系统来表示骨骼和关节,并制定了最佳控制问题(OCP),其目的是最大程度地降低生理动机的成本函数,而运动方程和进一步的非线性约束必须得到满足。所研究的生物力学运动是通过关节扭矩或通过希尔型肌肉力引起的。通过比较约束力,我们将文献中已知的几种成本函数与另一种成本函数进行了比较,涉及到对关节的影响。使用称为DMOCC(离散力学和约束系统的最佳控制)的直接转录方法来求解OCP,从而使我们受益于其结构保留公式,因为生成的最佳离散轨迹是辛动量保留。

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