AN OPTIMAL-CONTROL MODEL FOR MAXIMUM-HEIGHT HUMAN JUMPING
AN OPTIMAL-CONTROL MODEL FOR MAXIMUM-HEIGHT HUMAN JUMPING
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DOI：
10.1016/0021-9290(90)90376-e
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发表时间：
1990-01-01
影响因子：
2.4
通讯作者：
LEVINE, WS
中科院分区：
文献类型：
--
作者：
PANDY, MG;ZAJAC, FE;LEVINE, WS
为了了解肌肉间隙控制、身体各部分之间的惯性相互作用以及肌肉肌腱动力学如何协调人体运动，我们选择研究最大高度跳跃。 因为这种活动提出了一个相对明确的性能标准，如果适合最优控制理论的框架。 人体被建模为一个四段，平面，铰接联动，与相邻的链接连接在一起的无摩擦旋转。 驱动骨骼系统的是八个肌肉肌腱致动器，每个肌肉建模为三个元件，集总参数实体，与肌腱串联。 假设钢筋束是弹性的，其性质由应力-应变曲线定义。 肌肉的力学行为由Hill型收缩单元描述，包括串联和并联弹性。 驱动肌肉肌腱模型是兴奋-收缩（激活）动力学的一阶表示。 最优控制问题是最大限度地提高身体的质量中心达到的高度，身体节段，肌肉肌腱，和激活动力学，零垂直地面反作用力的升空，和限制的传入神经控制信号的幅度之间的限制，躺在零（无激励）和一个（全激励）。基于Mayne-Polak动态优化算法，找到了该问题的计算解。 定性比较模型的预测和以前报道的实验结果表明，该模型再现了最大高度蹲跳的主要特征（即肢体节段角位移，垂直和水平地面反作用力，肌肉活动的顺序，整体跳跃高度，和最后升空时间）。
To understand how intermuscular control, inertial interactions among body segments, and musculotendon dynamics coordinate human movement, we have chosen to study maximum-height jumping. Because this activity presents a relatively unambiguous performance criterion, if fits well into the framework of optimal control theory. The human body is modeled as a four-segment, planar, articulated linkage, with adjacent links joined together by frictionless revolutes. Driving the skeletal system are eight musculotendon actuators, each muscle modeled as a three-element, lumped-parameter entity, in series with tendon. Tendon is assumed to be elastic, and its properties are defined by a stress-strain curve. The mechanical behavior of muscle is described by a Hill-type contractile element, including both series and parallel elasticity. Driving the musculotendon model is a first-order representation of excitation-contraction (activation) dynamics. The optimal control problems is to maximize the height reached by the center of mass of the body subject to body-segmental, musculotendon, and activation dynamics, a zero vertical ground reaction force of lift-off, and constraints which limit the magnitude of the incoming neural control signals to lie between zero (no excitation) and one (full excitation). A computational solution to this problem was found on the basis of a Mayne-Polak dynamic optimization algorithm. Qualitative comparisons between the predictions of the model and previously reported experimental findings indicate that the model reproduces the major features of a maximum-height squat jump (i.e. limb-segmental angular displacements, vertical and horizontal ground reaction forces, sequence of muscular activity, overall jump height, and final lift-off time).