Title :
Learning Petri network and its application to nonlinear system control
Author :
Hirasawa, Kotaro ; Ohbayashi, Masanao ; Sakai, Singo ; Hu, Jinglu
Author_Institution :
Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan
fDate :
12/1/1998 12:00:00 AM
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 for realizing 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 capability 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; backpropagation; neural nets; nonlinear control systems; brain science; dynamic systems; functions distribution; learning Petri network; neural network; nonlinear crane control systems; nonlinear system control; numerical simulations; Biological neural networks; Brain modeling; Control system synthesis; Control systems; Cranes; Humans; Nonlinear control systems; Nonlinear systems; Numerical simulation; Power engineering and energy;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.735388