Inverse Problems in Mechatronic System Integration and Control

随着现有的机电一体化技术突飞猛进地发展，机电一体化系统的基本计算方法必须发展以跟上步伐。复杂机电系统的设计和实施在测量和控制方面提出了重要的公开问题，需要基于具体数学的系统方法。缺少的一环是认识到机电一体化系统集成中的许多未决问题是逆问题，即知识差距从“Z”流向“A”，类似于从终点跑到起点。鉴于机电一体化系统集成中的开放问题可以表示为逆问题，解决此类问题的成熟工具使我们能够物理地洞察复杂的测量和控制过程。因此，这种方法解释了虚拟传感器应该如何工作来推断关于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)应该如何通过协作控制来单独和作为一个整体工作。因此，研究计划的目标是将机电系统的反问题方法建立在机电系统集成的这两个关键领域的坚实科学基础上：虚拟传感：就像Inge Lehmann在不打开地球核心的情况下给我们提供了清晰的视图一样，机电系统的虚拟传感器被用来推断在不适宜居住的环境中可能无法访问或隐藏的信息。将开发一种基于模型的方法，以获得分布参数系统及其复杂行为的虚拟视图。协作控制：一群鸟或一群鱼可以以近乎完美的队形旅行，但他们能解决组合控制问题来做到这一点吗？机器人机械抓取的问题包括协调控制多个手指以实现类似的目标。将开发一个反问题工具箱，以提供必要的控制工具和理解，以开发实验室中的功能抓取机制。反问题理论在过去曾在工程上获得巨大成功，最显著的是在无损检测和热成像方面。它将表明，这一丰富的理论可以给我们提供新的见解，如测量和控制等老问题。该研究计划的成果将是一个工具箱，它将成为解决工业机器人、医疗机器人、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。为这项研究计划做出贡献的研究人员将被灌输数学工具和客观思维方式，以解决现代机电一体化必须提供的挑战性问题，即逆问题。

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.