用数据驱动反馈控制让可重构晶格结构更稳定精准。
Data-driven Feedback Control of Lattice Structures with Localized Actuation and Sensing
- 基于实时动态测量,用数据驱动方法实现闭环控制。
- 实验证明在少传感少执行下仍能完成稳定与追踪任务。
- 适合做智能材料、可重构机器人等领域的研究者参考。
将离散构件组装成晶格结构,可构建大型、异构且易于重构的物体,具备理想的质刚比。这类系统也被称为数字材料,由可纠错的离散单元构成。已有研究展示了多种主动结构甚至机器人系统,利用了离散晶格的可重构与轻质特性。然而,现有文献多采用开环控制,限制了系统性能。本文提出一种新型数据驱动反馈控制方法,结合实时系统动态测量,引入可驱动体元作为晶格结构的新执行手段。控制策略基于扩展动力模式分解(Extended Dynamical Mode Decomposition)算法,融合线性二次调节器(LQR)与科普曼模型预测控制(Koopman Model Predictive Control)。该方法无需预先了解系统结构,纯数据驱动。通过自研柔性晶格梁的实物实验,验证了其在仅少量感知与执行资源下,仍能有效完成稳定性保持与扰动抑制、以及参考轨迹跟踪等任务。
原文摘要 · Abstract (English)
Assembling lattices from discrete building blocks enables the composition of large, heterogeneous, and easily reconfigurable objects with desirable mass-to-stiffness ratios. This type of building system may also be referred to as a digital material, as it is constituted from discrete, error-correcting components. Researchers have demonstrated various active structures and even robotic systems that take advantage of the reconfigurable, mass-efficient properties of discrete lattice structures. However, the existing literature has predominantly used open-loop control strategies, limiting the performance of the presented systems. In this paper, we present a novel approach to feedback control of digital lattice structures, leveraging real-time measurements of the system dynamics. We introduce an actuated voxel which constitutes a novel means for actuation of lattice structures. Our control method is based on the Extended Dynamical Mode Decomposition algorithm in conjunction with the Linear Quadratic Regulator and the Koopman Model Predictive Control. The key advantage of our approach lies in its purely data-driven nature, without the need for any prior knowledge of a system's structure. We illustrate the developed method via real experiments with custom-built flexible lattice beam, showing its ability to accomplish various tasks even with minimal sensing and actuation resources. In particular, we address two problems: stabilization together with disturbance attenuation, and reference tracking.
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