Nonlinear Control System Using Learning Petri Network

Abstract

According to the recent knowledge of brain sience, it is suggested that there exists functions distribu tion in the brain, which means that different neurons are activated depending on which sort of sensory information the brain receives. We have already developed a learning network with functions distribution which is called Learn ing Petri Network(L.P.N.) and have also shown that this network could learn nonlinear and discontinuous mappings which Neural Network(N.N.) can not. In this paper, a more realistic application which has dynamic characteristics is studied. From simulation results of a nonlinear crane control system using L.P.N. controller, it is clarified that the control performance of L.P.N. controller is superior to that of N.N. controller.