Modeling and Control of Traffic Flow based on Hybrid Petri Net

Author(s):  
T Kato ◽  
T Kato ◽  
Y. K. Kim ◽  
T Suzuki
2014 ◽  
Vol 11 (1) ◽  
pp. 90-102 ◽  
Author(s):  
Maria Pia Fanti ◽  
Giorgio Iacobellis ◽  
Agostino Marcello Mangini ◽  
Walter Ukovich

2012 ◽  
pp. 393-408
Author(s):  
Gen’ichi Yasuda

The methods of modeling and control of discrete event robotic manufacturing cells using Petri nets are considered, and a methodology of decomposition and coordination is presented for hierarchical and distributed control. Based on task specification, a conceptual Petri net model is transformed into the detailed Petri net model, and then decomposed into constituent local Petri net based controller tasks. The local controllers are coordinated by the coordinator through communication between the coordinator and the controllers. Simulation and implementation of the control system for a robotic workcell are described. By the proposed method, modeling, simulation, and control of large and complex manufacturing systems can be performed consistently using Petri nets.


Author(s):  
Gen’ichi Yasuda

The methods of modeling and control of discrete event robotic manufacturing cells using Petri nets are considered, and a methodology of decomposition and coordination is presented for hierarchical and distributed control. Based on task specification, a conceptual Petri net model is transformed into the detailed Petri net model, and then decomposed into constituent local Petri net based controller tasks. The local controllers are coordinated by the coordinator through communication between the coordinator and the controllers. Simulation and implementation of the control system for a robotic workcell are described. By the proposed method, modeling, simulation, and control of large and complex manufacturing systems can be performed consistently using Petri nets.


Author(s):  
A. Abhishek ◽  
Manish Kumar ◽  
Devendra P. Garg

This paper presents comprehensive and unified strategies to model, analyze, and control flexible manufacturing systems (FMSs) in an uncertain and dynamic environment using Petri Net (PN) based modeling. The proposed methodology enables PN models to accept and assimilate online data at execution time. A measurement system consisting of distributed sensory sources suitable for manufacturing processes is designed and an interface is developed of that system with the modeling software (SHARPE) and MATLAB's Simulink to enable realtime data acquisition and processing. The proposed strategies enable online parameter estimation to impart adaptive and intelligent learning capabilities to PN models.


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