CAREER: Power Optimization in Autonomous Microsystems via Integrated Motion Control

职业：通过集成运动控制实现自主微系统的功率优化

• 批准号: 0954422
• 负责人: Kenn Oldham
• 金额: $ 40.01万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-15 至 2016-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0954422&HistoricalAwards=false
• 关键词: CAREER; Power; Optimization; Autonomous; Microsystems

The research objective of this Faculty Early Career Development (CAREER) award is to explore novel control strategies for minimizing power consumption of autonomous microsystems. Microsystems are engineered devices with sub-millimeter dimensions; at this scale, many phenomena become important that are ignored in larger devices, including many energy losses in circuitry. New control strategies will dramatically reduce total energy usage by coordinating motion control with active regulation of power electronics and sensor circuitry. These strategies will be based on switching control theory, where the various components of a microsystem are regulated through proper timing of a finite number of commands. These switching commands can be implemented especially efficiently in miniaturized systems. Switching control theory will be enhanced to provide robust performance in the presence of variation in the behavior of underlying physical components, and to adapt to changing conditions over time. Deliverables will include comprehensive controller design and optimization procedures, micro-scale component modeling tools, documentation of innovations in switching control theory, experimental verification on micro-robotic testbeds, engineering student education, and interactive on-line learning tools for secondary students. Successful realization of this research will increase understanding of fundamental trade-offs between power consumption and performance of interconnected micro-scale dynamic systems. The primary application is the control of insect-like terrestrial micro-robots, where small size dramatically limits power availability. Minimal-power control and optimization algorithms will be a major enabling step towards the creation of micro-robotic tools for emergency, health, and maintenance workers, and will have wider application to other microsystems such as unattended sensor nodes and implantable medical devices, where resource or energy conservation is critical. In the process, micro-robotics will be used as a theme for developing interactive in-class lessons and online programs teaching concepts such as work and energy to secondary students, with interactive online activities refined for broad dissemination over the Internet.

该学院早期职业发展（CAREER）奖的研究目标是探索新的控制策略，以最大限度地减少自主微系统的功耗。 微系统是具有亚毫米尺寸的工程设备;在这种规模下，许多现象变得重要，而这些现象在较大的设备中被忽略，包括电路中的许多能量损失。新的控制策略将通过协调运动控制与电力电子和传感器电路的主动调节来显著减少总能量使用。 这些策略将基于开关控制理论，其中微系统的各个组件通过有限数量的命令的适当定时来调节。 这些开关指令可以在小型化系统中特别有效地实现。 开关控制理论将得到加强，以便在基础物理组件的行为发生变化时提供稳健的性能，并适应随时间变化的条件。 这些内容将包括全面的控制器设计和优化程序、微尺度组件建模工具、开关控制理论创新的文档、微型机器人试验台的实验验证、工程学生教育以及中学生的交互式在线学习工具。这项研究的成功实现将增加相互关联的微尺度动态系统的功耗和性能之间的基本权衡的理解。 主要应用是控制昆虫类陆地微型机器人，其中小尺寸极大地限制了电源可用性。 最小功率控制和优化算法将是为紧急情况，健康和维护工作人员创建微型机器人工具的重要一步，并将更广泛地应用于其他微系统，如无人值守传感器节点和植入式医疗设备，其中资源或能源节约至关重要。 在此过程中，微型机器人将被用作开发互动课堂课程和在线课程的主题，向中学生教授工作和能源等概念，并改进互动在线活动，以便在互联网上广泛传播。