Inverse Problems in Mechatronic System Integration and Control
机电系统集成与控制中的反问题
基本信息
- 批准号:RGPIN-2022-05271
- 负责人:
- 金额:$ 2.04万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2022
- 资助国家:加拿大
- 起止时间:2022-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
As the available mechatronic technology grows with leaps and bounds, the underlying computational methods for mechatronic systems must develop to keep pace. The design and implementation of complex mechatronic systems poses important open problems in measurement and control that necessitate a systematic approach based on concrete mathematics. The missing link is the realization that many of the open problems in mechatronic system integration are inverse problems, i.e., knowledge gaps that flow from `Z' to `A', akin to running a race from finish to start. With this insight that the open problems in mechatronic system integration can be formulated as inverse problems, the well-established tools for solving such problems give us physical insight into complex measurement and control processes. This approach therefore explains how a virtual sensor should work to infer information about a system that cannot be directly measured, and how a group of robotic mechanical systems, such as a grasper with multiple digits, should behave both individually, and as a whole through collaborative control. The objective of the research program is therefore to put the inverse problem approach for mechatronic systems on a firm scientific foundation for these two key areas of mechatronic system integration: Virtual sensing: In much the same way as Inge Lehmann gave us a clear view of the inner core of the earth without cutting it open, virtual sensors for mechatronic systems are used to infer information that may be inaccessible or hidden in an inhospitable environment. A model-based approach will be developed for gaining a virtual view into distributed parameter systems and their complex behaviour. Collaborative Control: A flock of birds or school of fish can travel in near perfect formation, but do they solve combinatorial control problems to do so? The problem of robotic mechanical grasping involves the control of multiple digits in concert to accomplish similar goals. An inverse problem toolbox will be developed to provide the necessary control tools and understanding to develop a functional grasping mechanism in the lab. Inverse problem theory has been used in the past to great success in engineering, most notably in non-destructive testing and thermography. It will be shown that this rich theory can give us new insight into old problems such as measurement and control. The outcome of the research program will be a toolbox that will be an integral part of new measurement and control technology for practical problems such as industrial robotics, health care robotics, advanced manufacturing, and argrimechatronics. The researchers that contribute to this research program will be instilled with the mathematical tools and objective mode of thinking for solving the challenging problems that modern mechatronics has to offer, i.e., the inverse problems.
随着可用的机电一体化技术的突飞猛进,机电一体化系统的基础计算方法必须不断发展以跟上步伐。复杂机电系统的设计和实现在测量和控制方面提出了重要的开放性问题,需要基于具体数学的系统方法。缺少的环节是认识到机电系统集成中的许多开放问题都是逆问题,即从“Z”到“A”的知识差距,类似于从终点到起点进行一场比赛。认识到机电一体化系统集成中的开放问题可以被表述为逆问题,解决此类问题的成熟工具使我们能够对复杂的测量和控制过程进行物理洞察。因此,这种方法解释了虚拟传感器应如何工作来推断无法直接测量的系统的信息,以及一组机器人机械系统(例如具有多个手指的抓取器)应如何通过协作单独和作为一个整体进行行为控制。因此,该研究计划的目标是将机电一体化系统的反问题方法建立在机电一体化系统集成的这两个关键领域的坚实科学基础上: 虚拟传感:与 Inge Lehmann 给我们提供了清晰的视角一样,机电系统的虚拟传感器可以在不切开地球内核的情况下推断出在恶劣环境中无法访问或隐藏的信息。将开发基于模型的方法,以获得分布式参数系统及其复杂行为的虚拟视图。协作控制:一群鸟或鱼群可以以近乎完美的队形旅行,但它们是否解决了组合控制问题来做到这一点?机器人机械抓取的问题涉及多个手指的协调控制以实现类似的目标。将开发一个反问题工具箱,以提供必要的控制工具和理解,以在实验室中开发功能性抓取机制。反问题理论过去已在工程领域取得了巨大成功,尤其是在无损检测和热成像领域。事实证明,这种丰富的理论可以让我们对测量和控制等老问题有新的见解。该研究项目的成果将是一个工具箱,它将成为解决工业机器人、医疗保健机器人、先进制造和农业机电一体化等实际问题的新测量和控制技术的组成部分。参与该研究项目的研究人员将被灌输数学工具和客观思维模式,以解决现代机电一体化所提供的挑战性问题,即反问题。
项目成果
期刊论文数量(0)
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Harker, Matthew其他文献
Inverse Boundary Value Problems with Uncertain Boundary Values and Their Relevance to Inclinometer Measurements
- DOI:
10.1109/i2mtc.2014.6860725 - 发表时间:
2014-01-01 - 期刊:
- 影响因子:0
- 作者:
O'Leary, Paul;Harker, Matthew - 通讯作者:
Harker, Matthew
Feasibility of Cancer Clinical Trial Enrollment Goals Based on Cancer Incidence
- DOI:
10.1200/cci.19.00088 - 发表时间:
2020-01-24 - 期刊:
- 影响因子:4.2
- 作者:
Tran, George;Harker, Matthew;Zafar, S. Yousuf - 通讯作者:
Zafar, S. Yousuf
Harker, Matthew的其他文献
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{{ truncateString('Harker, Matthew', 18)}}的其他基金
Inverse Problems in Mechatronic System Integration and Control
机电系统集成与控制中的反问题
- 批准号:
DGECR-2022-00042 - 财政年份:2022
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Launch Supplement
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