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发帖数: 261 | 1 Abstract:
Various model-based control methods are currently used in control of
piezoelectric tubes, others such as internal model control and model
predictive control are anticipated to be employed soon. All these control
systems are designed based on black box models. However, systematic black
box modeling of piezoelectric tubes has been overlooked in the literature to
a large extent or has been presented in a too brief and faulty way. In this
article, a novel structure of artificial neural networks is used to model
and to assess the nonlinearity of piezoelectric actuators. Apart from
nonlinearity, other features of the achieved models like delay time,
sampling time, orders as well as system identification process are clearly
stated, and more importantly, it is clarified that different definitions of
accuracy are needed for different purposes of black box modeling, with
change in model features, the accuracy may decrease for one purpose (e.g.
predictive control) and increase for
another one (e.g. simulation). This highly critical point has never been
raised and addressed in modeling of piezoelectric tubes, and a definition of
accuracy which suits static systems/models has been widely used in the past
to assess models of piezoelectric tubes which are obviously dynamic.
Experimental results support the proposed modeling ideas.
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