Inverse Problems in Mechatronic System Integration and Control

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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.