Design and Implementation of Petri Net for Brain-Computer Interface System

Abstract

In this paper, we propose a new shared control method based on Petri net for the cooperative control of human intelligence and machine intelligence. Our method divides the brain-computer interface (BCI) system into different functional modules, adds control places to ordinary Petri nets to describe the results of each function, and simplifies the modeling process of Petri nets through the composition of nets. We first establish a Petri net model that contains EEG information, robot state information, and surrounding environment information. This model can be used to visually analyze the state and rules of the entire system. Then the Petri net-based brain-computer interface system is designed, and the simulation is carried out on the mobile robot simulation platform of MobileSim. The results show that the shared control method based on Petri net is reasonable and feasible. Modeling the BCI system through the Petri net method can better describe the state of the system, facilitate the analysis and improvement of the control rules of the system to improve the applicability of the BCI system.