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Learning Petri network and its application to nonlinear system control.

Hirasawa, K.; Ohbayashi, M.; Sakai, S.; Hu, J.

In: IEEE Trans. on Systems, Man, and Cybernetics - Part B, Vol. 28, No. 6, pages 781-789. 1998.

Abstract: According to recent knowledge of brain science, it is suggested that there exists `functions distribution', which means that specific parts exist in the brain to realize specific functions. This paper introduces a new brain-like model called learning Petri network (LPN) that has the capability of functions distribution and learning. The idea is to use Petri net to realize the functions distribution and to incorporate the learning and representing ability of neural network into the Petri net. The obtained LPN can be used in the same way as a neural network to model and control dynamic systems, while it is distinctive to a neural network in that it has the capacity of functions distribution. An application of the LPN to nonlinear crane control systems is discussed. It is shown via numerical simulations that the proposed LPN controller has superior performance to the commonly used neural network one.

Keywords: Petri nets, back-propagation algorithms, control systems, learning networks, neural networks.

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