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Augmenting Self-Stability: Height Control of a Bernoulli Ball via Bang-Bang Control

机译:增强自稳定性:通过Bang-Bang控制对伯努利球进行高度控制

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Mechanical self-stability is often useful for controlling systems in uncertain and unstructured environments because it can regulate processes without explicit state observation or feedback computation. However, the performance of such systems is often not optimised, which begs the question how their dynamics can be naturally augmented by a control law to improve performance metrics. We propose a minimalistic approach to controlling mechanically self-stabilising systems by utilising model-based, feedforward bang-bang control at a global level and self-stabilizing dynamics at a local level. We demonstrate the approach in the height control problem of a sphere hovering in a vertical air jet—the so-called Bernoulli Ball. After developing a model to study the system and theoretically proving global asymptotic stability, we present the augmented controller and show how to enhance performance measures and plan behaviour. Our physical experiments show that the proposed control approach has a reduced time-to-target compared to the uncontrolled system without loss of stability (ranging from a 2.4 to 4.4 fold improvement) and that we can plan sequences of target positions at will.
机译:机械自稳定性通常可用于在不确定和非结构化环境中控制系统,因为它可以调节过程而无需进行明确的状态观察或反馈计算。但是,此类系统的性能通常并未得到优化,这引出了一个问题,即如何通过控制定律自然地增强其动态性以改善性能指标。我们提出了一种极简主义的方法来控制机械自稳定系统,方法是在全球范围内利用基于模型的前馈爆炸控制,在局部水平上利用自稳定动力学。我们演示了一种方法,该方法用于在垂直喷气机中盘旋的球体(所谓的伯努利球)的高度控制问题。在开发了一个用于研究系统的模型并从理论上证明了全局渐近稳定性之后,我们提出了增强型控制器并展示了如何增强性能指标和计划行为。我们的物理实验表明,与不受控制的系统相比,所提出的控制方法可缩短目标时间,而不会损失稳定性(从2.4倍提高到4.4倍),并且我们可以随意计划目标位置的顺序。

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