Optimal Control of a Hybrid Rhythmic-Discrete Task: The Bouncing Ball Revisited
Optimal Control of a Hybrid Rhythmic-Discrete Task: The Bouncing Ball Revisited
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混合节奏离散任务的最优控制：重温弹跳球
DOI：
10.1152/jn.00600.2009
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发表时间：
2010-05-01
影响因子：
2.5
通讯作者：
Sternad, Dagmar
中科院分区：
文献类型：
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作者：
Ronsse, Renaud;Wei, Kunlin;Sternad, Dagmar
Ronsse R，WeK，Sternad D。节奏-离散混合任务的最优控制：弹跳球的再认识。神经生理学杂志103：2482-2493,2010。2010年2月3日首次出版；DOI：10.1152/jn.00600.2009。用球拍有节奏地弹跳球是一项混合任务，它结合了球拍的连续有节奏的驱动和控制球拍和球之间的离散碰撞事件。这项研究提供了实验数据和一个两层建模框架，明确地解决了控制的混合性质：第一个离散层计算击球时达到的状态，第二个连续层基于最优化原则平稳地将球拍驱动到期望的状态。这种混合模型的试验台是在一系列越来越慢的节奏下的任务表现。当减慢弹跳动作的节奏时，连续的循环被分成一系列离散的运动，中间穿插着停留时间，并被引导以达到预期的效果。对人类表现的分析表明，随着TEMPI变慢，表现指标的可变性越来越大，与球拍轨迹从近似正弦向不那么对称的速度剖面变化相关。模型仿真的匹配结果支持基于最优性的混合控制模型，从而表明最优性原理适用于球弹跳等复杂运动的感觉-运动控制。
Ronsse R, Wei K, Sternad D. Optimal control of a hybrid rhythmic-discrete task: the bouncing ball revisited. J Neurophysiol 103: 2482-2493, 2010. First published February 3, 2010; doi: 10.1152/jn.00600.2009. Rhythmically bouncing a ball with a racket is a hybrid task that combines continuous rhythmic actuation of the racket with the control of discrete impact events between racket and ball. This study presents experimental data and a two-layered modeling framework that explicitly addresses the hybrid nature of control: a first discrete layer calculates the state to reach at impact and the second continuous layer smoothly drives the racket to this desired state, based on optimality principles. The testbed for this hybrid model is task performance at a range of increasingly slower tempos. When slowing the rhythm of the bouncing actions, the continuous cycles become separated into a sequence of discrete movements interspersed by dwell times and directed to achieve the desired impact. Analyses of human performance show increasing variability of performance measures with slower tempi, associated with a change in racket trajectories from approximately sinusoidal to less symmetrical velocity profiles. Matching results of model simulations give support to a hybrid control model based on optimality, and therefore suggest that optimality principles are applicable to the sensorimotor control of complex movements such as ball bouncing.