Persistent Models for Complex Control Systems

2017 ◽  
pp. 167-175
Author(s):  
Shahab Ilbeigi ◽  
David Chelidze
Keyword(s):  
Control Systems ◽  
Complex Control

scholarly journals A Reusable Driving Engine for Complex Control Systems Based on Embedded TCP/IP

2015 ◽  
Author(s):  
Zhang Zhichun ◽  
Xiao Jingxin ◽  
Xu Wen ◽  
Zhao Zhenpen ◽  
Tang Shengquan ◽  
...  
Keyword(s):  
Control Systems ◽  
Complex Control

scholarly journals THE AUTOMATIC SYNTHESIS OF PETRI NETS BASED ON THE FUNCTIONING OF ARTIFICIAL NEURAL NETWORK

2021 ◽  
pp. 84-92
Author(s):  
A. A. Gurskiy ◽  
A. V. Denisenko ◽  
S. M. Dubna
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Automatic Control ◽  
Petri Nets ◽  
Control Systems ◽  
Automatic Synthesis ◽  
Temporal Characteristics ◽  
Complex Control ◽  
Automatic Control Systems ◽  
Artificial Neural

Context. The important task was solved during the scientific research related to the development of the methods for automatic synthesis of Petri nets while tuning up of the coordinating automatic control systems. The importance of development of these methods is due to the evolution of intelligent systems. These systems provide the automation of labor intensive processes in the particular case this is the tuning of the certain type of complex control systems. Objective. The purpose of the scientific work is to minimize the time and automation of process in tuning of the multilevel coordinating automatic control systems. Method. The principle of automatic synthesis of Petri nets and the implementation of certain algorithms for tuning complex control systems based on the functioning of an artificial neural network are proposed. The mathematical description of the method for changing the coefficients in neural connections of network in the synthesis of Petri nets is presented. Results. The experiments were conducted in the Matlab\Simulink 2012a environment. These experiments were bound to the joint functioning of an artificial neural network and Petri nets. The functioning of Petri nets was presented in the Matlab \ Simulink environment using Statflow diagrams. As a result of the experiments we have obtained the temporal characteristics of the functioning of artificial neural network providing the composition of Petri nets. The fundamental suitability of using artificial neural network to provide the automatic composition of Petri nets was determined on the basis of analysis of temporal characteristics. Conclusion. The problem linked to the development of system for the joint functioning of neural network and Petri nets for the formation of algorithms and sequential calculations was solved in this work. Thus the method of automatic synthesis of Petri nets and the method of developing of the certain algorithms based on the functioning of a neural network were further developed.

Coupling electromagnetic (FE) models to multidomain simulator to analyse eletrical drives and complex control systems

2010 ◽  
Vol 59 (3-4) ◽  
pp. 189-201
Author(s):  
Mariusz Jagieła ◽  
Tomasz Garbiec
Keyword(s):  
Control Systems ◽  
Maxwell Equations ◽  
Reference Data ◽  
Electrical Machine ◽  
Power Electronic ◽  
Two Dimensional ◽  
Simulation Approach ◽  
Complex Control ◽  
Dimensional Finite Element ◽  
Power Electronic Converter

Coupling electromagnetic (FE) models to multidomain simulator to analyse eletrical drives and complex control systemsThis work presents the co-simulation approach to the analysis of control systems containing detailed models of electromagnetic and electromechanical converters. In this method of analysis the attention is paid to the whole system and not only to its electromagnetic part. The latter is described by equations resulted from the two-dimensional finite element discretisation of the Maxwell equations, and is coupled weakly with the remaining part of the system. The simulation is carried out in Matlab/Simulink environment wherein the coupling is realised through the S-function. Example results regarding simulation of the operation of the control system of an electrical machine and the operation of a power electronic converter are presented and compared with available reference data.

Mathematical simulation of complex control systems

1972 ◽  
Vol 11 (10-11) ◽  
pp. 973-977
Author(s):  
A. N. Doroshenko ◽  
A. G. Shigin
Keyword(s):  
Mathematical Simulation ◽  
Control Systems ◽  
Complex Control
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