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Intermittent predictive control of man and machine

人与机器的间歇预测控制

基本信息

批准号：
EP/F068514/1
负责人：
Ian Loram
金额：
$ 35.74万
依托单位：
Manchester Metropolitan University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FF068514%2F1
关键词：
Intermittent predictive control man machine

项目摘要

For fifty years, the servo mechanism, a simple, reactive, continuous feedback system, has been used as a model of human neural control systems. The PID servo is the most well known example which uses positional and velocity feedback to stabilise the variable of importance. It has always been known that the nervous system is more sophisticated than this. We are all aware that we anticipate: sometimes the error in our expectations catches us out, such as when we use too much force to lift a suitcase that is lighter than we expected. There has been increasing acceptance that the nervous system predicts our world and predicts how neural signals will be converted into bodily movement. As a model of motor control, the servo paradigm has been increasingly replaced by the optimal control or continuous predictive control paradigm which is founded on the engineering control methodology of internal models, prediction and optimisation. While it is more sophisticated and richer in its expression, the continuous predictive control paradigm is still inconsistent with several aspects of biological behaviour. Biological control is inherently variable. For humans, the temporal response to stimuli is inconsistent, the reformulating of immediate goals is highly flexible, and the bandwidth, i.e. frequency limit, of meaningful control is rather low. These neural features are not natural outcomes of the continuous control paradigm derived from engineering insight, which has been designed precisely to negate these limitations of human control and produce control which is temporally consistent, with high bandwidth, highly specified function and hence minimal goal flexibility. This proposal's power derives from a new type of engineering control methodology known as Intermittent predictive control . Intermittent predictive control provides a spectrum of possibilities between the two extremes of continuous-time and discrete-time control: the control signal consists of a sequence of (continuous-time) parameterised trajectories whose parameters are adjusted intermittently. It is different from discrete-time control in that the control is not constant between samples; it is different from continuous-time control in that the trajectories are reset intermittently. As a class of control theory, intermittent predictive control is more general than continuous control and provides a new paradigm incorporating continuous predictive and optimal control with intermittent, open loop (ballistic) control. This new intermittent predictive control paradigm has important technological applications. Consequently there is a need to develop the concept, theory and system identification of these controllers. This new paradigm is also intuitively similar to human physiological control systems in that low bandwidth, flexible, variable control is a natural product of the mechanism. We intend to discover whether human postural mechanisms are best explained by a continuous PID type of controller or an intermittent control process. The powerful corrective responses that occur when posture is perturbed can be explained on the basis of high bandwidth continuous feedback. However, we question whether such mechanisms dominate in the exquisitely fine control of unperturbed, skilled and learned postural activities such as standing. If the intermittent predictive control paradigm is applicable, then natural postural balance is correctly reinterpreted as centrally modulated, voluntary control like any other form of movement. Clarification of this issue will have important implications for diverse healthcare topics including the rehabilitation of spinally injured patients who are no longer able to stand and the diagnosis of risk factors in elderly patients with a history of falling.We aim to incorporate our biological insights into the design of engineering controllers that mimic the real-time flexibility of the human nervous system.

50年来，伺服机构，一个简单的，反应性的，连续反馈系统，一直被用作人类神经控制系统的模型。PID伺服是最著名的例子，它使用位置和速度反馈来稳定重要变量。人们一直知道，神经系统比这更复杂。我们都知道我们的预期：有时我们的预期错误会让我们措手不及，比如当我们用太大的力气提起一个比我们预期的要轻的手提箱时。人们越来越多地接受神经系统预测我们的世界，并预测神经信号将如何转化为身体运动。作为电机控制的一种模式，伺服模式已越来越多地被最优控制或连续预测控制模式所取代，这是建立在内部模型，预测和优化的工程控制方法学基础上的。虽然它是更复杂和更丰富的表达，连续预测控制范式仍然是不一致的生物行为的几个方面。生物防治具有内在的可变性。对于人类来说，对刺激的时间反应是不一致的，对直接目标的重新制定是高度灵活的，并且有意义的控制的带宽（即频率限制）相当低。这些神经功能不是来自工程洞察力的连续控制范式的自然结果，其被精确地设计为否定人类控制的这些限制，并产生时间上一致的控制，具有高带宽，高度指定的功能，因此具有最小的目标灵活性。这一建议的力量来自一种新型的工程控制方法，称为间歇预测控制。间歇预测控制提供了连续时间和离散时间控制两个极端之间的可能性谱：控制信号由一系列（连续时间）参数化轨迹组成，这些轨迹的参数被间歇地调整。它不同于离散时间控制，因为控制在样本之间不是恒定的;它不同于连续时间控制，因为轨迹是间歇性重置的。间歇预测控制作为一类控制理论，比连续控制更具有普遍性，它提供了一种将连续预测和最优控制与间歇开环（弹道）控制相结合的新的控制方法。这种新的间歇预测控制模式具有重要的技术应用。因此，有必要发展这些控制器的概念，理论和系统识别。这种新的范例也直观地类似于人类生理控制系统，因为低带宽，灵活，可变的控制是该机制的自然产物。我们打算发现人类的姿势机制是否是最好的连续PID型控制器或间歇控制过程的解释。当姿势被扰动时发生的强大的校正响应可以在高带宽连续反馈的基础上解释。然而，我们怀疑这种机制是否在对不受干扰的、熟练的和学习过的姿势活动（如站立）的精细控制中占主导地位。如果间歇性预测控制范式是适用的，那么自然的姿势平衡被正确地重新解释为中枢调制，像任何其他形式的运动一样的自愿控制。这个问题的澄清将对各种医疗保健主题产生重要影响，包括脊柱损伤患者的康复，不再能够站立和老年患者的危险因素的诊断与历史falling.We的目标是将我们的生物学见解纳入工程控制器的设计，模仿人类神经系统的实时灵活性。