Self-Sensing Actuation and Control with Shape Memory Alloys

使用形状记忆合金进行自感知驱动和控制

• 批准号: 0089977
• 负责人: Lynda Brinson
• 金额: $ 23.58万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-15 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0089977&HistoricalAwards=false
• 关键词: Self; Sensing; Actuation; Control; Shape

Cate Brinson, Michael Peshkin, Bruce Wilson Northwestern University Shape memory alloys (SMAs) have been used in a variety of actuation, energy-absorbing, and sensing applications. The key feature of this material is its ability to undergo large seemingly-plastic strains and subsequently recover these strains when a load is removed or the material is heated. This unique ability occurs due to a reversible thermoelastic phase transformation between austenite and martensite. The key feature allows SMAs to serve as very compact actuators. As SMAs can be used for both material-stiffening and energy-absorption, they have generated much interest in the smart structures field. Further, no other material or device can generate significant tensile forces over a large displacement while occupying such a small volume. A second useful feature of many SMAs is a change in resistivity with a change in strain. The change in resistivity as an SMA undergoes strain has enabled investigators to use them as coarse position sensors. The coarseness is due to a complex relationship between resistivity and the material state and its coupling with mechanical load and temperature. Given the material characteristics above, economical, power-dense self-sensing-actuation (SSA) can be achieved with shape memory alloys. However, the nonlinear nature of SMA actuation and sensing, incomplete understanding of SMA thermomechanical response and the lack of suitable models for control result in an under-utilization of this useful material as an actuator, sensor, and SSA. In this research, a focused effort will be targeted at (1) improving the characterization of SMAs for a sensing and control context, (2) refining material modeling, (3) developing model-based control algorithms, and (4) demonstrating these in hardware to advance the understanding and range of applications of SMAs as actuators, sensors, and SSAs.

西北大学形状记忆合金（SMA）已被用于各种驱动，能量吸收和传感应用。 这种材料的关键特征是它能够承受大的塑性应变，并且随后在移除载荷或加热材料时恢复这些应变。 这种独特的能力是由于奥氏体和马氏体之间的可逆热弹性相变而发生的。 该关键特性允许SMA用作非常紧凑的致动器。由于形状记忆合金具有材料刚化和能量吸收的双重作用，因此在智能结构领域引起了广泛的关注。 此外，没有其他材料或装置可以在占据如此小的体积的同时在大的位移上产生显著的张力。许多SMA的第二个有用特征是电阻率随应变变化而变化。 SMA经历应变时电阻率的变化使研究人员能够将其用作粗略的位置传感器。 粗糙度是由于电阻率和材料状态之间的复杂关系及其与机械载荷和温度的耦合。 考虑到上述材料特性，可以利用形状记忆合金实现经济的、功率密集的自感测致动（SSA）。 然而，SMA致动和感测的非线性性质、SMA热机械响应的不完全理解以及用于控制的合适模型的缺乏导致这种有用材料作为致动器、传感器和SSA的利用不足。在这项研究中，重点工作将集中在（1）改善SMA的表征，用于传感和控制环境，（2）完善材料建模，（3）开发基于模型的控制算法，以及（4）在硬件中演示这些，以促进SMA作为执行器，传感器和SSA的应用范围和理解。