POSSIBILITIES OF CYBER-PHYSICAL APPROACH TO STUDYING FREQUENCY PROPERTIES OF CLOSED SYSTEM WITH INCOMPLETE INFORMATION ABOUT CONTROL OBJECT MODEL

The article considers a method of reducing the time spent on the experimental study of the frequency properties of an object with an unknown mathematical model by using the cyber-physical approach to the automation of the experiment. Nonparametric estimates of unknown frequency characteristics of an object are received from experimental data on the reaction of the object's output to the input harmonic signal in the form of a mixture of sinusoidal signals of different frequencies. To divide the output signal into components corresponding to each frequency, a computer technology is used that implements an optimization procedure for finding the values of both real and imaginary frequency characteristics, according to the frequencies represented in the harmonic input signal. The method is also suitable for accelerated evaluation of the frequency characteristics of an object with an unknown delay. There are considered the aspects of frequency properties estimation in the problem of closed system stability analysis, which is supposed to control an object with incomplete information about its model using a series-connected proportional-integral controller. The results of quick estimating the frequency characteristics of the object are used to identify the parameters of its transfer function. To solve the parameterization problem, there are used automation tools for calculating the transfer function according to data on the points of frequency characteristics implemented as part of the open-access computer mathematics system Scilab. There is given an example illustrating the possibilities of developing a control system using a reduced-order object model, as one of the applications of the results of parametric identification of the transfer function

Modeling Complex Systems by Structural Invariants Approach

When modeling complex systems, we usually encounter the following difficulties: partiality, large amount of data, and uncertainty of conclusions. It can be said that none of the known approaches solves these difficulties perfectly, especially in cases where we expect emergences in the complex system. The most common is the physical approach, sometimes reinforced by statistical procedures. The physical approach to modeling leads to a complicated description of phenomena associated with a relatively simple geometry. If we assume emergences in the complex system, the physical approach is not appropriate at all. In this article, we apply the approach of structural invariants, which has the opposite properties: a simple description of phenomena associated with a more complicated geometry (in our case pregeometry). It does not require as much data and the calculations are simple. The price paid for the apparent simplicity is a qualitative interpretation of the results, which carries a special type of uncertainty. Attention is mainly focused (in this article) on the invariant matroid and bases of matroid (M, BM) in combination with the Ramsey graph theory. In addition, this article introduces a calculus that describes the emergent phenomenon using two quantities—the power of the emergent phenomenon and the complexity of the structure that is associated with this phenomenon. The developed method is used in the paper for modeling and detecting emergent situations in cases of water floods, traffic jams, and phase transition in chemistry.

Some Foundational Issues in Quantum Information Science

This chapter has three Parts. Part 1 attempts to analyze the concept “information” (in some selected contexts where it has been used) in order to understand the consequences of representing and processing information, quantum mechanically. There are at least three views on ‘Information’ viz., ‘Semantic Naturalism’, ‘the Quantum Bayesian Approach’ and ‘Information is Physical’ approach. They are then critically examined and at last one is given preference. Part 2 of the chapter then goes on to discuss the manner in which the study and quantification of “Qubit” (Quantum bit), Superposition and Entanglement, comprise the three pillars of Quantum Information Science and enable the discipline to develop the theory behind applications of quantum physics to the transmission and processing of information. In Part 3 we take up the issue that although it might appear bewildering, the physical approach to Quantum Information Science is equally proficient in dealing with its impact on the questions of “consciousness,” “freewill” and biological questions in the area known as “bioinformatics.”