Controlling the Remaining Useful Lifetime using Self-Optimization (bibtex)
by , , ,
Abstract:
Self-optimizing mechatronic systems offer possibilities well beyond those of traditional mechatronic systems. Among these is the adaptation of the system behavior to the current situation. To do so, they are able to choose from different working points, which are pre-calculated using multiobjective optimization and are thus Pareto-optimal with regard to the chosen objective functions. In this contribution, a method is presented that allows to continuously control the system degradation by adapting the behavior of a selfoptimizing system throughout its complete lifetime. The current remaining useful lifetime is estimated and then related to the spent lifetime and the desired useful lifetime. Using this information, a reliability-related objective is prioritized using a closed-loop control, which in turn is used to determine the working point of the self-optimizing system. This way, the desired useful lifetime can be achieved. To exemplify the setup of the controller structure and to demonstrate the adaptation of the system behavior, a dynamic model of a clutch system is used. It can be seen that the closed loop controller is able to correct for external perturbations, such as changed requirements, as well as changed system parameters. This way, the modeled system is able to achieve the desired lifetime reliably.
Reference:
Meyer, T.; Sondermann-Wölke, C.; Kimotho, J. K.; Sextro, W.: Controlling the Remaining Useful Lifetime using Self-Optimization. Chemical Engineering Transactions, volume 33, 2013.
Bibtex Entry:
@ARTICLE{Meyer2013c,
  howpublished = {Journal},
  author = {Tobias Meyer AND Christoph Sondermann-W{\"o}lke AND James Kuria Kimotho
	AND Walter Sextro},
  title = {Controlling the Remaining Useful Lifetime using Self-Optimization},
  journal = {Chemical Engineering Transactions},
  year = {2013},
  volume = {33},
  pages = {625-630},
  abstract = {Self-optimizing mechatronic systems offer possibilities well beyond
	those of traditional mechatronic systems. Among these is the adaptation
	of the system behavior to the current situation. To do so, they are
	able to choose from different working points, which are pre-calculated
	using multiobjective optimization and are thus Pareto-optimal with
	regard to the chosen objective functions. In this contribution, a
	method is presented that allows to continuously control the system
	degradation by adapting the behavior of a selfoptimizing system throughout
	its complete lifetime. The current remaining useful lifetime is estimated
	and then related to the spent lifetime and the desired useful lifetime.
	Using this information, a reliability-related objective is prioritized
	using a closed-loop control, which in turn is used to determine the
	working point of the self-optimizing system. This way, the desired
	useful lifetime can be achieved.
	
	To exemplify the setup of the controller structure and to demonstrate
	the adaptation of the system behavior, a dynamic model of a clutch
	system is used. It can be seen that the closed loop controller is
	able to correct for external perturbations, such as changed requirements,
	as well as changed system parameters. This way, the modeled system
	is able to achieve the desired lifetime reliably.},
  bdsk-url-1 = {http://www.aidic.it/cet/13/33/105.pdf},
  bdsk-url-2 = {http://dx.doi.org/10.3303/CET1333105},
  doi = {10.3303/CET1333105},
  url = {http://www.aidic.it/cet/13/33/105.pdf}
}
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