Learning Petri network and its application to nonlinear system control

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.

An intelligent control system construction using high-level time Petri net and Reinforcement Learning

“…Here, the degree m of data (t i , Q i (p,t i )) is not less than data number n of formula (3). According to least squares method, we have (5).…”

“…Recently, there are some researches for making the Petri net is equipped with learning capability. A learning Petri net model which co mb ines Petri net with neural network is proposed in [3]. This learn ing Petri net model can realize an input-output mapping through Petri net's weight function which is adjusted just like an artificial neural network.…”

Construction and Application of Learning Petri Net

“…The global variables are optimized and colored Petri net is updated according to these global variables. A learning Petri net model which combines Petri net with a neural network is proposed by Hirasawa et al, and it was applied to nonlinear system control [10]. In our former work [5,6], a learning Petri net model has been proposed based on reinforcement learning (RL).…”

Intelligent Decoupled Control for Linear Induction Motor Drive

“…In practice, it is desirable to design a systematic control methodology with simple inference framework for ensuring the stability and robustness of the overall system. For the last decades, Petri net (PN) has been developed into a powerful tool for modeling, analysis, control, optimization, and implementation of various engineering systems [17]− [19]. In this study, the basic concept of a PN incorporated into a traditional FNN is used to organize a robust PFNN control system for the motion control of the LIM drive.…”