Coordinated Natural Rhythmic Movements by Distributed Biological Oscillators

分布式生物振荡器协调自然节律运动

• 批准号: 0654070
• 负责人: Carl Knospe
• 金额: --
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0654070&HistoricalAwards=false
• 关键词: Coordinated; Natural; Rhythmic; Movements; Distributed

The overall goal of this project is to understand the biological control mechanism underlying natural rhythmic movements observed during animal locomotion, and to establish a design principle for engineering applications. In particular, we focus on the distributed control mechanism realized by neuronal oscillators called the central pattern generators (CPGs), and aim to establish a design theory for CPG-based feedback controllers to robustly achieve natural rhythmic movements of mechanical systems. We hypothesize that entrainment to a natural mode of oscillation can be robustly achieved for the closed-loop system by placing a CPG unit in the feedback loop between each collocated sensor/actuator pair of a multi-degree-of-freedom, lightly damped, mechanical system. We will develop analytical formulas for the control design parameters to achieve an oscillation with a given frequency and mode shape, using the method of multivariable harmonic balance (MHB). We will then examine whether the hypothesis is supported by the predictions from the MHB analysis. Feedback controls are essential for many engineering applications in which we desire to adjust movements of a physical system. Current technologies enable extremely fast and accurate motions with the aid of computer-controls. However, such control devices are only good at following a command, and lack sophistication to "think" what to do when the situation changes. For instance, we would walk differently on ice so that we don't slip or fall, but a walking robot would not be able to adjust its motion. This is because the motion is planned ahead assuming a nominal situation, and a controller forces the robot to move as planned even when the situation changes. In biological systems, appropriate motions are planned in real time by CPGs, based on sensory feedback information. This research will uncover the biological mechanism underlying this integration of motion planning and controls, enabling designs of robust and adaptable engineering systems. The synergistic effect between neuroscience and control engineering will accelerate advance of both fields. In particular, the knowledge from neuroscience will help to uncover engineering principles, while the results from control engineering will in turn provide new predictions for biological mechanisms that can be tested through physiological experiments.

该项目的总体目标是了解动物运动过程中观察到的自然节律运动的生物控制机制，并建立工程应用的设计原则。特别是，我们专注于分布式控制机制实现的神经元振荡器称为中央模式发生器（CPGs），并旨在建立一个设计理论的CPGs为基础的反馈控制器，以实现机械系统的自然节奏运动的鲁棒性。我们假设夹带到一个自然的振荡模式，可以鲁棒地实现闭环系统，通过放置一个CPG单元之间的每个并置的传感器/致动器对的多自由度，轻阻尼，机械系统的反馈回路。我们将开发控制设计参数的解析公式，以实现具有给定频率和模式形状的振荡，使用多变量谐波平衡（MHB）的方法。然后，我们将检查该假设是否得到MHB分析预测的支持。 反馈控制是必不可少的许多工程应用中，我们希望调整运动的物理系统。目前的技术能够在计算机控制的帮助下实现非常快速和精确的运动。然而，这样的控制设备只擅长于遵循命令，而缺乏当情况发生变化时“思考”该做什么的复杂性。例如，我们会在冰上以不同的方式行走，这样我们就不会滑倒或摔倒，但行走机器人无法调整其运动。这是因为，假设标称情况，预先规划运动，并且控制器强制机器人即使在情况改变时也按计划移动。在生物系统中，基于感觉反馈信息，CPG在真实的时间中规划适当的运动。这项研究将揭示这种运动规划和控制集成的生物机制，使设计强大和适应性强的工程系统成为可能。神经科学与控制工程之间的协同效应将促进这两个领域的发展。特别是，神经科学的知识将有助于揭示工程原理，而控制工程的结果将反过来为可以通过生理实验进行测试的生物机制提供新的预测。