Functional stability of technological processes based on nonlinear dynamics with the application of neural networks

Abstract

The processes of transformation of global information infrastructure and large-scale automation of production lead to the actual merger of automated production, data exchange and production technologies into a single self-regulatory system with minimal or no human intervention in the production process. Currently, there is a mass introduction of cyberphysical systems into production with the simultaneous application of the results obtained in the fields of artificial intelligence, robotics, the Internet of Things and so on. Implementing the goal of developing methods for organizing production processes of metal processing at machine-building enterprises using neural networks, the processes of global transformation of IT infrastructure were studied against the background of mass introduction of cyberphysical systems and breakthroughs in artificial intelligence and technological processes. The characteristics of the behavior of complex technical systems that implement the property of functional stability of such systems are studied. The processes of metal processing by cutting are characterized taking into account the peculiarities of the influence of deformation hardening, plastic deformations, self-oscillations and chaotic dynamics that occur in machining centers. Methods of application of neural networks in modeling of processes of mechanical processing of metals by cutting are described. A universal technique for constructing neural network models of the machining process on the basis of an artificial counter-propagation neural network is given. Based on the analysis, an intelligent system of analysis and forecasting of the dynamic stability of the technological process of cutting using parallel calculations, which guarantees the fulfillment of the necessary conditions to ensure the functional stability of the production process.

Mathematical Model of Cyber Risks Management Based on the Expansion of Piecewise Continuous Analytical Approximation Functions of Cyber Attacks in the Fourier Series

“…Musienko [18], respectively. The stability of the information system, in terms of functioning with the conditions of external and internal destabilizing factors, was studied in [19]. External and internal destabilizing factors include mean failures, failures of system modules, mechanical damage, thermal effects, and errors of service personnel.…”

Approximation of Functions of the Classes CβψHα by Linear Methods Summation of Their Fourier Series

“…We should note that linear summation methods of Fourier series have a number of advantages over traditional Fourier series summation methods: first, they can be more accurate than traditional methods; secondly, they can be more resistant to noise; and third, they can be more adaptive to different signals. This is extremely important when modeling processes for which the functional stability of complex technical systems must be guaranteed [21][22][23]. Methods of constructing the asymptotic solution of differential equations are important for hydrodynamic problems [24], for mathematical models of processes that describe phenomena where the action of internal and external destabilizing factors of an impulsive nature takes place [25,26], for heat conduction equations [27], etc.…”