Application of statistical clustering to mathematical description and control of continuous processes with discrete event output

Author(s):  
V.A. Skormin
1995 ◽  
Vol 117 (3) ◽  
pp. 235-240
Author(s):  
V. A. Skormin ◽  
C. R. Herman ◽  
L. J. Popyack

Statistical clustering is applied for mathematical description of a surface mount assembly process. The clustering model, intended for process control applications, defines the correspondence between various outcomes of the process and particular regions in the space of process variables. An adaptive version of the clustering model is presented. Prediction, regime selection and control procedures, utilizing the clustering model, are formulated.


Author(s):  
Calin Ciufudean

Cyber Security Model of Artificial Social System Man-Machine takes advantage of an important chapter of artificial intelligence, discrete event systems applied for modelling and simulation of control, logistic supply, chart positioning, and optimum trajectory planning of artificial social systems. “An artificial social system is a set of restrictions on agents` behaviours in a multi-agent environment. Its role is to allow agents to coexist in a shared environment and pursue their respective goals in the presence of other agents” (Moses & Tennenholtz, n.d.). Despite conventional approaches, Cyber Security Model of Artificial Social System Man-Machine is not guided by rigid control algorithms but by flexible, event-adaptable ones that makes them more lively and available. All these allow a new design of artificial social systems dotted with intelligence, autonomous decision-making capabilities, and self-diagnosing properties. Heuristics techniques, data mining planning activities, scheduling algorithms, automatic data identification, processing, and control represent as many trumps for these new systems analyzing formalism. The authors challenge these frameworks to model and simulate the interaction of man-machine in order to have a better look at the human, social, and organizational privacy and information protection.


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.


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