RU2741138C1 - Method of identifying object as system - Google Patents

Abstract

FIELD: physics.

SUBSTANCE: invention relates to computer engineering and specifically to automatic control. Fixed parameters of the object are represented as vectors of parameters of the resource object of resource/energy and acquisition of resource/energy by the object. List of resource consumption vectors is generated and the resource is obtained by the object interacting with the environment and interacting with each other within the boundaries of the object itself. Formulated list of vectors of the obtained, processed, stocked, consumed resource/energy by the object on a condition of a non-negative summation of summation of all vectors at any moment in time is controlled. All the transient processes of the resource are found from the functions of the system as characteristics of the linear process, which are limited by the equality of the incoming resource to its resource consumption with the condition of preserving a non-negative or zero balance. Resource transfer of system processes to each other is detected.

EFFECT: method enables reducing the time for identifying an object as a system, improving the accuracy of prediction of the state of the object, improving the efficiency of the selected control method on the object.

3 cl, 30 dwg, 2 tbl

Description

The invention relates to computer technology, automatic control and can be used both for searching and identifying objects according to their ability to generate / consume a resource (energy), and for replenishing descriptions of individual objects, as well as for replenishing the very set of object descriptions, developing tools and measures for influence (control) of the state of an object with incomplete information about its structure, the structure of the external environment and its disturbances.

A known method for identifying operating objects in control systems (RF patent RU 2 686 257 C1 G05B 19/045, G05B 15/02, G06F 17/10, G06F 17/18.) Is used to create an artificial intelligence system that automatically determines the causes of occurrence and localization of incipient defects in various modes of operation of remote monitoring objects, by detecting and recognizing the occurrence of anomalies in their work due to: a) fixing the space of parameters characterizing the object, b) determining the structure of interaction of the object's parameter space, c) introducing the space of indicators of the target evaluation contour object, d) introducing a contour of influence (control) on the object by the space of the control actions of the observer (regulator) and the goals of the object.

Disadvantage of the method:

1. the object of analysis is predefined, no identification is required. With a low correlation of values, the close to normal distribution law of standardized residuals of parameters does not work, i.e. values that have a strong random nature of origin cannot be estimated and predicted reliably by artificial intelligence: a) decreased identification of the object;

2. it cannot be used to identify an object if the differential equation describes its state with insufficient accuracy: a) decrease in object identification;

3.cannot be applied to an object identified as a system in modes of a sharp change in the variation characteristics of the parameters of its processes (does not take into account the change in the role of the parameter in the system that characterizes the object as a system): b) decrease in the accuracy of determining the structure of interaction of the object's parameter space;

4. does not take into account the one-time (instantaneous) change in the internal structure of the object identified as a system (does not take into account the change in the matrix that specifies the nature of the relationship of parameters characterizing the object as a system): b) decrease in the accuracy of determining the structure of interaction of the object's parameter space;

5.the properties of the parameters of the space of new systems are not checked by the result of the process of unification / separation, duplication of any part of it or the complete reproduction of the system with autonomous or dependent on the base system operating modes of the new systems formed (separation / unification of space and the matrix of interaction of parameters of the structure of the system) : d) deterioration of the accuracy and efficiency of management;

6. there is no mechanism for automatic identification of an object as a system after changing the dimension of the observed object (the change in dimension is not recorded): d) deterioration of the accuracy and efficiency of control;

7. it is impossible to automatically rebuild the matrix of the control structure, when the dimension of the observed system changes: b) decrease in the accuracy of determining the structure of interaction of the object parameter space;

8. if the external random disturbance is unknown, then the identification of the object is performed without taking into account the influence of external influences: a) decrease in the efficiency of object identification);

9. a universal indicator is not formed that characterizes the state of the system and allows one to compare systems of different sizes in one area and other areas with each other for the analysis and assessment of the synergistic result: d) deterioration of the accuracy and efficiency of management;

10. the inevitability of generating an error of false synonymy in the absence of signs that uniquely identify objects, situations, phenomena: a) decrease in the efficiency of object identification);

11. ambiguity of the sets and values used for control in case of random errors or system parameters: there is an element, but there is no data on it, and vice versa: d) deterioration of the accuracy and efficiency of control.

There is a known method for identifying control channels of objects with applying test signals to predictable operating controls (RU 2 271 561 C2 G05B 23/00) to improve the identification accuracy by determining typical situations with corresponding regulatory and forecasting errors with the corresponding statistical characteristics and by assigning an appropriate algorithm predicting the trajectories of changes in time of the control of a technological object and the trajectories of the vector of its output values due to: a) fixing the space of parameters characterizing the object, b) determining the structure of the interaction of the space of object parameters, c) introducing the space of indicators of the contour for evaluating the goals of the object, d) introducing an action contour (control) on the object by the space of the control actions of the observer (regulator) and the objectives of the object.

Disadvantages:

1. does not take into account the parameters of the system with low values of the characterizing processes occurring (the frequency of falling into the interval). Interconnections of parameters outside the confidence interval are not identified as elements of the system (parts of the object) (distortion of the space characterizing the object as a system): a) decrease in the efficiency of object identification);

2. does not take into account the one-time (instantaneous) change in the internal structure of the object identified as a system (does not take into account the change in the matrix that sets the nature of the relationship of parameters characterizing the object as a system): b) decrease in the accuracy of determining the structure of interaction of the object's parameter space;

3.the properties of the parameters of the space of new systems are not checked by the result of the process of unification / separation, duplication of any part of it, or complete reproduction of the system with autonomous or dependent on the base system modes of operation of the newly formed systems (separation / unification of space and the matrix of interaction of parameters of the structure of the system) : d) deterioration of the accuracy and efficiency of management;

4. it is impossible to apply for the analysis of systems of different nature (biological objects, economic objects, space objects, etc.): c) complication of the procedure for setting goals);

5. it is impossible to compare one description from a set of two or more objects of subsystems and systems (biological objects, economic objects, technical objects, space objects, etc.) - problems of homonymy: d) deterioration of the accuracy and efficiency of control;

6. a universal indicator is not formed that characterizes the state of the system and allows one to compare systems of different sizes in one area and other areas with each other for the analysis and assessment of the synergistic result: d) deterioration of the accuracy and efficiency of management;

7. the inevitability of generating an error of false synonymy in the absence of signs that uniquely identify objects, situations, phenomena: a) decrease in the efficiency of object identification);

8. ambiguity of the sets and values used for control in case of random errors or system parameters: there is an element, but there is no data on it, and vice versa: d) deterioration of the accuracy and efficiency of control.

There is a known method for identifying a linearized dynamic object RU 2 256 950 C2 G06F 17/18, G05B 17/02, G05B 17/02) for structural and parametric identification of a linearized object with predetermined values of the measured input-output signals of the object, which automatically determines the structure and unknown parameters of the mathematical model of the object, improving the quality and reliability of the results of modeling the control object, and on their basis determine the development of the object's processes in the course of its functioning due to: a) fixing the space of parameters characterizing the object, b) determining the structure of the interaction of the object's parameter space, c) introducing the space of indicators of the contour for evaluating the goals of the object, d) introducing the contour of influence (control) on the object by the space of control actions of the observer (regulator) and the goals of the object.

Disadvantages:

1. does not take into account the parameters of the system with low values of the characterizing processes occurring (the frequency of falling into the interval). Interconnections of parameters outside the confidence interval are not identified as elements of the system (parts of the object) (distortion of the space characterizing the object as a system): a) decrease in the efficiency of object identification);

2. it cannot be applied to an object identified as a system in modes of a sharp change in the variation characteristics of the parameters of its processes (does not take into account the change in the role of a parameter in the system that characterizes the object as a system): a) decrease in the efficiency of object identification);

3. does not take into account a one-time (instant) change in the internal structure of an object identified as a system (does not take into account the change in the matrix that defines the nature of the relationship of parameters characterizing the object as a system): b) decrease in the accuracy of determining the structure of interaction of the object's parameter space;

4.the properties of the parameters of the space of new systems are not checked by the result of the process of unification / separation, duplication of any part of it or complete reproduction of the system with autonomous or dependent on the base system modes of operation of the newly formed systems (separation / unification of space and matrix of interaction of parameters of the structure of the system) : d) deterioration of the accuracy and efficiency of management;

5. there is no mechanism for automatic identification of an object as a system after changing the dimension of the observed object (the change in dimension is not recorded): a) decrease in the efficiency of object identification);

6. it is impossible to automatically rebuild the matrix of the control structure, when the dimension of the observed system changes: d) deterioration of the accuracy and efficiency of control;

7. it is impossible to automatically rebuild the control space when the dimension of the observed system changes: d) deterioration of the accuracy and efficiency of control;

8. it is impossible to take into account the experience of managing a mechanism that creates a control action: c) complication of the procedure for setting goals);

9. it is impossible to compare one description from a set of two or more objects of subsystems and systems (biological objects, economic objects, space objects, etc.) - problems of homonymy: d) deterioration of the accuracy and efficiency of control;

10. a universal indicator is not formed that characterizes the state of the system and allows one to compare systems of different sizes in one area and other areas with each other for the analysis and assessment of the synergistic result: d) deterioration of the accuracy and efficiency of management;

11. the inevitability of generating an error of false synonymy in the absence of signs that uniquely identify objects, situations, phenomena: a) decrease in the efficiency of object identification);

12. ambiguity of the sets and values used for control in case of random errors or system parameters: there is an element, but there is no data on it, and vice versa: d) deterioration of the accuracy and efficiency of control.

Closest to the proposed method is:

The closest in technical essence to the proposed is the method of integral indicators described in non-patent documents:

Masaev S.N. "Methodology for a comprehensive assessment of management decisions in production systems with the use of correlation adaptometry": dis. ... Cand. tech. Sciences: 05.13.06: protected 03.25.11: approved. 11/25/11. Siberian Federal University, - Krasnoyarsk, 2011 .-- 214 p. In this work, the object is identified as a system due to: a) fixing the space of parameters characterizing the object, b) determining the structure of the interaction of the object's parameter space, c) introducing the space of indicators of the contour for evaluating the goals of the object, d) introducing a contour of influence (control) on the object by the space control actions of the observer (regulator) and the objectives of the object.

Disadvantages:

1. integral indicators and indicators of adaptometry are calculated according to the parameters of the system outside the confidence interval, thereby artificially limiting the dimension of the identified object as a system: a) decrease in the efficiency of object identification);

2.the properties of the parameters of the space of new systems are not checked by the result of the process of unification / separation, duplication of any of its parts or complete reproduction of the system with autonomous or dependent on the base system modes of operation of the newly formed systems (separation / unification of space and the matrix of interaction of parameters of the structure of the system) : d) deterioration of the accuracy and efficiency of management;

3. there is no mechanism for automatic identification of an object as a system after changing the dimension of the observed object (the change in dimension is not registered): a) a decrease in the identification of the object;

4. it is impossible to automatically rebuild the control structure matrix when the dimension of the observed system changes: d) decrease in control accuracy;

5. it is impossible to automatically rebuild the control space when the dimension of the observed system changes: d) decrease in control accuracy;

6. it is impossible to take into account the experience of controlling the mechanism that creates a control action: d) decrease in control accuracy;

7. it is impossible to apply for the analysis of systems of different nature (biological objects, technical objects, space objects, etc.) (part of the space describing the object does not fall into the characteristics of the object under study): c) complication of the goal setting procedure);

8. it is impossible to compare one description of one control method from a set of two or more objects of subsystems and systems (biological objects, technical objects, space objects, etc.) - problems of homonymy d) decrease in control accuracy;

9. a universal indicator is not formed that characterizes the state of the system and allows one to compare systems of different sizes of one area and other areas with each other for the analysis and assessment of a synergistic result without taking into account its significance d) decrease in control accuracy;

10. the inevitability of generating an error of false synonymy in the absence of signs that uniquely identify objects, situations, phenomena: a) decrease in the efficiency of object identification);

11. ambiguity of the sets and values used for control in case of random errors or system parameters: there is an element, but there is no data on it, and vice versa: d) decrease in control efficiency.

The purpose of the invention is to improve the accuracy, efficiency: identification of an observed object of any nature (biological, technical, socio-economic, space, mixed, etc.) when combined with any type of object, clones, copies of an object, other independent or dependent objects of a similar type or mixed and increasing the efficiency, accuracy (control) of the impact on their state, with incomplete or complete information about their structure, with various perturbations of the parameters of the external environment as a system.

The technical result is a way to identify an object as a system (of any nature: space, biological, technical, economic, etc.) to control its states, change its physical form, change the structure of internal relationships of elements, physical properties: when interacting with other systems (any nature: space, biological, technical, economic, etc.) division into one or more systems dependent on the original system or independent of the original system while maintaining control of the original system or another system or systems themselves, or the autonomous operation of all systems each from a friend or autonomous in various versions, including from the source system, combining with another dependent or independent source system, or combining with other dependent or independent source systems or systems with each other with modes of parallel operation, combining, separation, interchange of existing functional capabilities of systems with the possibility of their development or without the possibility of their development by interacting systems, clones or with the transfer of a limited set of functional capabilities of systems with the possibility of their development or non-development between systems, clones, by identifying the space of parameters characterizing the object, determining the structure of the interaction of the object's parameter space, introducing space indicators of the contour for evaluating the goals of the object, introducing the contour of influence (control) on the object by the space of the control actions of the observer (controller) and the goals of the object, characterized in that the fixed parameters of the object are represented as vectors of parameters of energy consumption and energy receipt by the object, sorting the vectors of energy consumption by the object and obtaining energy by an object interacting with the external environment and interacting with each other within the boundaries of the object itself, determining the amount of energy received, processed, stored, consumed by the object is greater than zero, determining everything x of transient energy processes by the functions of the system as a linear process, limited by the equality of the incoming energy to its energy balance in the object, the identification of the object as a system, the state of which is characterized by an analytical function and expressed by semantic indicators that take into account the parameters of the system, including those not included in the confidence intervals hypotheses to be tested, registration or prediction of the interchange of energy of its processes among themselves, between a clone of the system, copies of the system, transient processes of unification / separation, its separate independent parts and the external environment in a single semantics of the chosen method of influencing the system (control), predicting their state, control with our influence on them or not, reducing the time of their identification and forecasting, increasing the accuracy of their identification and forecasting, improving the method of managing them.

The method is as follows

- пространство наблюдаемых переменных при учете данных характеризующих объект,

-

- вектор параметров оперативного учета объекта для наблюдения. Если необходимо идентифицировать объект как систему, то происходит старт работы алгоритма и по стрелке 1.0.1 через узел 01 и стрелку 1.0.2 информация о объекте поступает в блок 1.1. Из алгоритма 1 по стрелке 1 поступает на узел 01 сигнал

- функция наблюдения любых параметров за объектом и по стрелке 1.0.2 в блок 1.1. В блоке 1.1 наблюдаемое пространство

данных переводим в

- фазовое пространство параметров объекта из

-

- вектор фазовых переменных, определяющих состояние объекта.

- параметр расхода или получения энергии элемента объекта. По стрелке 3 в блок 1.2 поступает

и проверяется наличие значений

-приток энергии и

-расход энергии и их взаимосвязь через матрицу

-

, определяющая внутреннюю структуру взаимодействия

с условием

. Если условие блока 1.2 не выполняется, то по стрелке 4 через узел 1.5 и стрелку 4.1

попадает в блок 1.3. В блоке 1.3 находится и доопределяется матрица

. В блоке 1.3 вырабатывается такая матрица

, которая позволит хотя бы одному параметру

поступления энергии найти параметр расхода ресурса

. Из блока 1.3 по стрелке 5 сигнал

поступает на проверку в блок 1.3.1. Блок 1.3.1 проверяет характеризуется полностью параметрами структуры

объект или нет. Если нет, то

из блока 1.3.1 по стрелке 2 через узел 01 и стрелку 1.0.2 попадает в блок 1.1. В блоке 1.3.1 если да, то по стрелке 6 через узел 03

через стрелку 8 попадает в блок 1.4. Если проверка в блоке 1.2 положительная, то переходим по стрелке 7 в узел 03 и по стрелке 8 в блок 1.4. В блоке 1.4 где

делятся на параметры/элементы

непосредственно участвующие в обмене энергией с внешней средой, а именно характеризующие события приносящие/расходующие энергию объекта, развивающие новые качеств объекта, элементы выступающие проводниками для высвобождения энергии в объекте или переводящие ее в запас энергии объекта. Далее значения

суммируются по процедуре

до общего показателя баланса энергии

:

. Значение

через стрелку 9 попадает в блоке 1.6 на проверку

. Если значение

отрицательное, то по стрелке 10 попадает в узел 1.5, от него по стрелке 4.1 в блок 1.3. Если значение

положительное, то через стрелку 11 попадает в блок 1.7. В блоке 1.7 идентификация переходных состояний энергии

по переходной матрице

чтобы получить систему линейных уравнений (СЛУ). Матрицей

характеризуются все возможные переходные состояния объекта в

ограниченные структурой перехода энергии внутри объекта и при контакте с внешней средой, также перехода энергии на изменение структуры перехода энергии в будущем, энергией разделения на другие объекты, энергией объединения с другими объектами и энергией сохранения структуры. В блоке 1.8 проверяется полученную систему линейных уравнений на условие

. Если условие блока 1.8 выполняется, то по стрелке 14 переходим в блок 1.10 через узел 1.9. В узле 1.9 добавляется метод воздействия (управления) выбранный наблюдателем и/или управляющим для объекта и цели объекта, поступающий по стрелке 16 в блок 1.10. В блоке 1.10 вырабатываем контур управления (воздействия) пространство управления

- пространство управляющих воздействий на объект,

-

- вектор воздействий, структура управления

где

процедура устанавливающая соответствие матрицы структуры объекта

в структуру управления объектом

.

и получаем данные в разрезе первого блока идентификации

. Формируем будущие состояния объекта

с учетом влияния параметров внешней среды

. Из

понятно что

-

-вектор фазовых переменных, определяющих состояние объекта при значения выработанных алгоритмом управления. Задаем

-

матрица, определяющая структуру наблюдателя. Тогда и

,

или

,

. Также структура наблюдателя определяется с учетом целей наблюдения за объектом.

- пространство целей воздействий (управления),

-

- вектор целевых значений параметров функционирования объекта при воздействии управлении (плановые и нормативные показатели объекта).

- пространство аналитических оценок функционирования объекта из пространств аналитических оценок поступления энергии в объект и расхода энергии объектом,

-

- вектор аналитических оценок;We have

- the space of observable variables when taking into account the data characterizing the object,

-

- vector of parameters of operational accounting of an object for observation. If it is necessary to identify an object as a system, then the algorithm starts operation and along arrow 1.0.1 through node 01 and arrow 1.0.2 information about the object enters block 1.1. From Algorithm 1, Arrow 1 sends a signal to node 01

- the function of observing any parameters for the object and along the arrow 1.0.2 to block 1.1. In block 1.1 observable space

data is translated into

- phase space of parameters of an object from

-

- vector of phase variables that determine the state of the object.

- parameter of consumption or energy production of an element of an object. Arrow 3 enters block 1.2

and the presence of values is checked

- energy supply and

- energy consumption and their relationship through the matrix

-

defining the internal structure of interaction

with the condition

... If the condition of block 1.2 is not met, then along arrow 4 through node 1.5 and arrow 4.1

falls into block 1.3. In block 1.3, the matrix is found and redefined

... In block 1.3 such a matrix is generated

which will allow at least one parameter

energy input find the resource consumption parameter

... From block 1.3 on arrow 5 signal

goes to block 1.3.1 for verification. Block 1.3.1 checks fully characterized by structure parameters

object or not. If not, then

from block 1.3.1 along arrow 2 through node 01 and arrow 1.0.2 it enters block 1.1. In block 1.3.1, if yes, then along arrow 6 through node 03

through arrow 8 it enters block 1.4. If the check in block 1.2 is positive, then go along arrow 7 to node 03 and along arrow 8 to block 1.4. In block 1.4 where

divided into parameters / elements

directly involved in the exchange of energy with the external environment, namely, characterizing the events that bring / consume the energy of the object, develop new qualities of the object, elements that act as conductors for the release of energy in the object or transfer it into the energy reserve of the object. Further values

summed up by procedure

to the overall energy balance

:

... Value

through arrow 9 gets into block 1.6 for verification

... If the value

negative, then along arrow 10 it falls into node 1.5, from it along arrow 4.1 into block 1.3. If the value

positive, then through arrow 11 it enters block 1.7. In block 1.7, the identification of transient energy states

by transition matrix

to obtain a system of linear equations (SLE). Matrix

all possible transient states of the object in

limited by the structure of energy transfer inside the object and in contact with the external environment, also the transfer of energy to change the structure of the energy transfer in the future, the energy of separation into other objects, the energy of unification with other objects and the energy of preserving the structure. Block 1.8 checks the resulting system of linear equations for the condition

... If the condition of block 1.8 is fulfilled, then along arrow 14 go to block 1.10 through node 1.9. In node 1.9, a method of action (control) is added, chosen by the observer and / or the manager for the object and the object's goal, which is sent by arrow 16 to block 1.10. In block 1.10, we develop a control loop (influence) control space

- the space of control actions on the object,

-

- vector of impacts, management structure

Where

procedure for matching a matrix to an object structure

to the object management structure

...

and get the data in the context of the first identification block

... We form the future states of the object

taking into account the influence of environmental parameters

... Of

it is clear that

-

- vector of phase variables that determine the state of the object at the values generated by the control algorithm. We set

-

matrix defining the structure of the observer. Then and

,

or

,

... Also, the structure of the observer is determined taking into account the objectives of observing the object.

- the space of the goals of influences (control),

-

- the vector of target values of the parameters of the object's functioning under the influence of control (planned and standard indicators of the object).

- the space of analytical estimates of the functioning of the object from the spaces of analytical estimates of the energy input into the object and the energy consumption of the object,

-

- vector of analytical estimates;

In block 1.10, we obtain a mathematical model of the object described by the equation:

.

...

:According to the resulting model, the syntax of action (control), the goals of the object, a system is formed

:

Where

- переходные функции системы, имеют в общем случае следующий вид:

- transient functions of the system, generally have the following form:

;Where

;

- функция наблюдения при оперативном управлении, определяющая параметры, доступные для наблюдения и имеющая вид:

- the monitoring function during operational control, which determines the parameters available for observation and has the form:

- функция анализа функционирования системы в предшествующие моменты времени, имеющая вид:

- the function of analyzing the functioning of the system in previous moments of time, which has the form:

- функция анализа прогнозных значений функционирования системы в будущие моменты времени, имеющая вид:

- the function of analyzing the predicted values of the functioning of the system at future points in time, which has the form:

and with conditionally optimal control

можно задать линейным векторным уравнением.When managing a production system, the function

can be specified by a linear vector equation.

The control action in operational management can be represented as.

or

- регулятор системы, вырабатывающий управляющее воздействие в зависимости от отклонения

фактических выходных параметров от целевых значений.Where

- system regulator that generates a control action depending on the deviation

actual outputs from target values.

передается в блок 1.11. В блоке 1.11 выполняем расчет семантических показателей через аналитическую функцию (4), (4а)

, которая позволяет получать аналитические оценки состояния системы.Arrow 17 identifies the object as a system

passed to block 1.11. In block 1.11, we perform the calculation of semantic indicators through the analytical function (4), (4а)

, which allows you to obtain analytical assessments of the state of the system.

гр. яз.), семантический показатель - показатель, обозначающий отношения элементов системы между собой и с факторами внешней среды.Traditionally, the word semantics is used in linguistics to study the semantic meaning of a language. As a term, it was first used by the French philologist and historian Michel Breal. Further in the text we will use the semantic term (

gr. lang.), a semantic indicator is an indicator that denotes the relationship of the elements of the system with each other and with environmental factors.

за

предыдущих тактов. Параметр

будем называть глубиной анализа. Получим матрицу.In the proposed approach, to form the observer function, we use the values of the vector of phase variables

per

previous measures. Parameter

will be called the depth of analysis. Let's get a matrix.

, выполняем следующую замену переменных:1. Let's center and normalize the elements that form the columns of the matrix

, we perform the following change of variables:

,

,

,

,

Where

2. Denote

and calculate

Where

and calculate

называются коэффициентами ковариации между переменными

и

в момент времени

, а матрица

- ковариационной матрицей между фазовыми переменными в момент времени t при глубине анализа k.The quantities

are called the coefficients of covariance between the variables

and

at the moment

and the matrix

- the covariance matrix between the phase variables at time t at the depth of analysis k.

называются коэффициентами корреляции между переменными

и

в момент времени

, а матрица

- корреляционной матрицей между фазовыми переменными в момент времени

при глубине анализа

.The quantities

are called the correlation coefficients between the variables

and

at the moment

and the matrix

- the correlation matrix between the phase variables at the time

at depth of analysis

...

равны единице, т.е.

для всех

и всех

, а остальные элементы находятся в диапазоне от -1 до +1 (

).In view of the introduced notation (13), (14), the diagonal elements of the matrix

are equal to one, i.e.

for all

and all

and the rest of the elements are in the range -1 to +1 (

).

и ковариации

матриц

и

на основе прогнозных значений фазовых переменных

за

будущих тактов.Similarly to formulas (13), (13a), the correlation coefficients are calculated

and covariance

matrices

and

based on predicted values of phase variables

per

future ticks.

Correlation matrices (13) are used to construct correlation graphs of the system, visually displaying the relationship between the parameters of the system.

Consider the matrix as an observer function:

and as a matrix prediction function:

The functions of the observer can serve as a semantic assessment of the dynamics of the system; it makes it possible to analyze the behavior of a multidimensional system, tracing the emerging trends of change caused by control or external influence, as well as predicting them.

мы и будем рассматривать в качестве функции наблюдаемой системы (16).Correlation matrix of phase variables

we will consider it as a function of the observed system (16).

As will be shown below, this function of the observer can serve as a semantic assessment of the dynamics of the system, it makes it possible to analyze the behavior of a multidimensional system, tracking the emerging trends of change caused by control or external influence.

и для всех

.Based on the foregoing, the initial data array (13) and, accordingly, the matrices are adjusted

and for everyone

...

(правила аналитической функций (4), (4а) распространяются,

это упрощение для

и

), для дальнейшего анализа, выделены следующие показатели корреляционного напряжения за прошлые периоды производственной системы:

- сумма абсолютных значений коэффициентов корреляции

-й функции с прочими,

- сумма отрицательных значений коэффициентов корреляции и

- сумма положительных значений,

- сумма значений коэффициентов корреляции, взятых с учетом знаков.Based

(the rules of the analytic functions (4), (4a) apply,

this is a simplification for

and

), for further analysis, the following indicators of the correlation stress for the past periods of the production system are highlighted:

- the sum of the absolute values of the correlation coefficients

-th function with others,

is the sum of negative values of the correlation coefficients and

- the sum of positive values,

- the sum of the values of the correlation coefficients, taken with the signs.

рассчитываются на заданном временном интервале T и, как уже говорилось, характеризуют связность каждой функции в корреляционном графе.All four meanings

are calculated over a given time interval T and, as already mentioned, characterize the connectivity of each function in the correlation graph.

In addition, for the study of the system as a whole, the total ratings of the entire system (corresponding to the general connectivity of the correlation graph) are of interest.

по семантическим показателям. Если выбираемые пороговые значения

не соблюдаются, то через стрелку 22 на узел 1.13. Из 1.13 по стрелке 21 на узел 1.15 и по стрелке 28 через узел 1.19 и стрелку 31 в алгоритм 1 для получения новых данных для идентификации объекта как системы. Параллельно из узла 1.13 по стрелке 24 в узел 1.16 и дальше по стрелке 20 в узел 1.5. Из узла 1.5 по стрелке 4.1 в блок 1.3. для уточнения матрицы

. Если условие симметричности выполняется в узле 1.12, то по стрелке 23 система поступает в блок 1.14 для расчета остальных семантических показателей по правилам аналитической функций (4) - по прошлым значениям, (4а) - по будущим значениям:Next, the system goes along arrow 18 to block 1.12 for checking

by semantic indicators. If selectable thresholds

are not observed, then through arrow 22 to node 1.13. From 1.13 along arrow 21 to node 1.15 and along arrow 28 through node 1.19 and arrow 31 to algorithm 1 to obtain new data to identify the object as a system. In parallel, from node 1.13 along arrow 24 to node 1.16 and further along arrow 20 to node 1.5. From node 1.5 along arrow 4.1 to block 1.3. to refine the matrix

... If the symmetry condition is satisfied at node 1.12, then along arrow 23 the system enters block 1.14 to calculate the remaining semantic indicators according to the rules of analytical functions (4) - according to past values, (4а) - according to future values:

1. Experience (foresight of the forecasting center)

Where dif is a configurable parameter (system experience).

2. The sum of positive and negative values

- признак, по которому происходит группировка пространства

.Where

- the sign by which the space is grouped

...

3. Indicator of the structure of energy exchange between the elements of the system with the external environment:

- признак, по которому происходит группировка пространства

.Where

- the sign by which the space is grouped

...

4. Indicator of the structure of energy exchange within the system:

- признак, по которому происходит группировка пространства

,

- величина сдвига периода для анализа.Where

- the sign by which the space is grouped

,

- the value of the period shift for analysis.

5. Indicator of system operation cycles:

- глубина анализа (дальновидность центра),

- depth of analysis (foresight of the center),

- автокорреляция функции,

.

- autocorrelation function,

...

- выбираемый номер рассчитываемого периода.

.

- selectable number of the calculated period.

...

6. Indicator of the influence of environmental parameters on the operation of system elements:

7. The indicator of the identity of the influencing parameters of the external environment on the operation of system elements:

You can calculate any statistical indicators and apply methods of control theory, MSET (Multivariate State Estimation Technique), Kernel Regression, Kernel Regression, Support Vector Machine (SVM), Similarity Based Modeling (SBM) , neural networks, fuzzy logic, main components or boosting decision trees since the object is identified as a linear system.

A statistical indicator will be a semantic indicator when, through the analytical function (4) and (4a), it can be represented as a set of positive statistical indicators and negative statistical indicators.

It is necessary to achieve symmetry of the phase trajectories of the observed parameters Fig. 2, Fig. 3, Fig. 13.

The calculated values from block 1.14 along arrow 25 fall into block 1.17 to check the condition. If you want to repeat the algorithm, then along arrow 27 to node 1.15 and along arrow 28 through node 1.19 and arrow 31 to algorithm 1. If not required, then along arrow 29 the data is transferred to node 15 and further along arrow 28 through node 1.19 and arrow 31 into algorithm 1. If the algorithm is not necessary to repeat, then the obtained semantic indicators through arrow 26, node 1.18 and further to arrow 29, node 1.15, arrow 28, node 1.19, arrow 31 are fed to algorithm 1 for further control of the object as a system. Arrow 30 disables the algorithm.

The essence of the invention is as follows.

With regard to real objects, an example of which is diagnostics of the state of a biological object that has the property of self-organization, its response to the applied control action will significantly depend on the state of the object, and the significant nonlinearity of its characteristics affects. As a rule, the control system is always close to the stability boundary for the entire period of the object's existence. At the same time, a small control aimed at deteriorating the state of the object can lead to the appearance of inappropriate situations and even death. So, in the treatment of patients with the same stage of the disease, one patient has a recovery, and the second has a deterioration in the general condition. This forces the medical staff to stop the course of treatment for the second patient and spend time on additional examination of the patient.

With regard to real objects, an example of which is the management of an economic object with the property of self-organization, its reaction to the applied control action will significantly depend on the state of the object, and the significant nonlinearity of its characteristics and parameters of the external environment affect. As a rule, the control system is often not close to the stability boundary for the entire period of the object's existence. Usually, the larger the object, the higher the stability limit and the more unattainable due to poor automation of the processes being performed. At the same time, management aimed at improving the state of the object can lead to the emergence of inappropriate situations and even the termination of the operation of the economic object. So, when the goal is realized, the point of its achievement is shifted indefinitely, the forecasting accuracy decreases. This forces the personnel to spend time revising the state of the object, considering new predicted values of the state of the object and the goal, and spending additional resources. It is almost impossible to take into account the influence of external factors.

With regard to real objects, an example of which is the control of a technical process that has the property of self-organization, its reaction to the applied control action will significantly depend on the state of the object, and the significant nonlinearity of its characteristics affects. As a rule, the control system is always close to the border of stability at high-tech stages of material processing (metals, composites, chemical solutions, etc.). At the same time, an accidental small control aimed at deteriorating the state of the object can lead to the appearance of inappropriate situations and even death. So, with an intense violation of technology at this stage, it leads to an avalanche accumulation of defective products. This forces you to stop the production process, remove the waste and repair the damaged section.

With regard to real objects, an example of which is diagnostics of the state of a space body with the property of self-organization, its response to the applied control action will significantly depend on the state of the object, and the significant nonlinearity of its characteristics affects. As a rule, the control system is always close to the stability limit in critical operating modes (all types of radiation, extremely low and high temperatures, etc.). At the same time, an accidental small control aimed at deteriorating the state of the object can lead to the appearance of inappropriate situations and even breakdown. So, with an intense loss of structural elasticity and hardness, the destruction of the object. This delays the design time for promising space objects or accidents with high material costs.

With regard to real objects, an example of which is diagnostics of the state of a space body with the property of self-organization, its response to the applied control action will significantly depend on the state of the object, and the significant nonlinearity of its characteristics affects. As a rule, the control system is always close to the stability limit in critical operating modes (all types of radiation, extremely low and high temperatures, etc.). At the same time, an accidental small control aimed at deteriorating the state of the object can lead to the appearance of inappropriate situations and even breakdown. So, with an intense loss of physical properties, structural elasticity, hardness, destruction of the object, etc. This delays the design time for promising space objects or accidents with high material costs.

With regard to real objects, an example of which is the process of changing the geometric shape and physical properties of the object itself, which has the property of self-organization, its reaction to the applied control action will significantly depend on the new state of the object, and the significant nonlinearity of its characteristics affects. As a rule, the control system is always close to the stability limit in all operating modes. At the same time, an accidental small control aimed at deteriorating the state of the object can lead to the appearance of inappropriate situations and even breakdown. So, with an intense loss of structural elasticity and hardness, the object is destroyed. This delays the design time for promising space objects or accidents with high material costs.

With regard to real objects, an example of which is the process of functional work with an implant of another object that has the property of self-organization, their reaction to the applied control action will significantly depend on the new state of objects, and the significant nonlinearity of their characteristics affects. As a rule, the control system is always close to the stability limit in all operating modes. At the same time, random small control and the influence of environmental factors, aimed at deteriorating the state of the object, can lead to the appearance of non-target situations and even breakdown. So, with an intense loss of properties of the implant, the operation of the entire element or object is disrupted. This leads to poisoning or other negative consequences, stopping the operation of the facility or costly repairs, or its removal.

With regard to promising objects, an example of which is the process of managing an object of different nature (technical, economic, space, biological, memory of different forms and properties, etc.) and the ability of an object of different nature (technical, economic, space, biological, memory of different forms and properties, etc.) to self-copying, combining with similar objects of different nature (technical, economic, space, biological, memory of different forms and properties, etc.) and division into objects of different nature (technical, economic, space, biological, memory of different forms and properties, etc.), possessing the property of self-organization, their reaction to the applied control action will significantly depend on the new state of objects of different nature (technical, economic, space, biological, memory of different forms and properties, etc.). and it is affected by the significant nonlinearity of their characteristics. As a rule, the control system is always close to the stability limit in all modes of operation and transient processes. At the same time, random small control and the influence of environmental factors aimed at deteriorating / improving the state of the object can lead to the emergence of non-target situations and the failure of the entire object of various nature (technical, economic, space, biological, memory of various forms and properties, etc.). etc.). So, with an intensive loss of the properties of the implant, the operation of the entire element or object is disrupted. Leads to unpredictable violations of work regimes associated with great damage and loss of life.

Consider example 1. The considered object is self-organizing, consumes energy to ensure the supply of new energy, ensuring the achievement of its goals under the influence of the parameters of the external environment. The structure of the object is unpredictable, but measurable, it is possible to influence the object, control. During the activity of the object, the number of functions that it performs in each period changes. The object can change its organizational structure and is influenced by the parameters of the external environment. As a result, the number of functions of the enterprise may increase, or may decrease. The observed dimension of the object used for control is different for each period. The object is divided into two objects by going to the mode of the parent object and the child object, or independent modes of operation of objects. After a while, the objects are combined into one object. The object is subject to modes of restriction of its activities.

данных переводим в

- фазовое пространство параметров объекта из

-

- вектор фазовых переменных, определяющих состояние объекта.

- параметр расхода или получения энергии элемента объекта (Фиг 4). По стрелке 3 в блок 1.2 поступает

и проверяется наличие значений

-приток энергии и

-расход энергии и их взаимосвязь через матрицу

-

, определяющая внутреннюю структуру взаимодействия

с условием

. Если условие блока 1.2 не выполняется, то по стрелке 4 через узел 1.5

попадает в блок 1.3. В блоке 1.3 находится и доопределяется матрица

. В блоке 1.3 вырабатывается такая матрица

, которая позволит хотя бы одному параметру

дохода ресурсов найти параметр расхода ресурса

. Из блока 1.3 по стрелке 5 сигнал

поступает на проверку в блок 1.3.1. Блок 1.3.1 проверяет характеризуется полностью параметрами

объект или нет. Если нет, то

из блока 1.3.1 по стрелке 2 через узел 01 попадает в блок 1.1. Если да, то по стрелке 6 через узел 03

попадает в блок 1.4. Если проверка в блоке 1.2 положительная, то переходим по стрелке 7 в узел 03 и по стрелке 8 в блок 1.4. В блоке 1.4 где

делятся на параметры/элементы

непосредственно участвующие в обмене энергией с внешней средой, а именно характеризующие события приносящие/расходующие энергию объекта, развивающие новые качеств объекта, элементы выступающие проводниками для высвобождения энергии в объекте или переводящие ее в запас. Далее значения

суммируются по процедуре

до общего показателя баланса энергии

:

. Значение

через стрелку 9 попадает в блоке 1.6 на проверку

. Если значение

отрицательное, то по стрелке 10 попадает в узел 1.5, от него по стрелке 4.1 в блок 1.3. Если значение

положительное, то через стрелку 11 попадает в блок 1.7. В блоке 1.7 идентификация переходных состояний энергии

по переходной матрице

чтобы получить систему линейных уравнений (СЛУ). Матрицей

характеризуются все возможные переходные состояния объекта в

ограниченные структурой перехода энергии внутри объекта и при контакте с внешней средой, также перехода энергии на изменение структуры перехода энергии в будущем, энергией разделения на другие объекты, энергией объединения с другими объектами и энергией сохранения структуры.In block 1.1 observable space

data is translated into

- phase space of parameters of an object from

-

- vector of phase variables that determine the state of the object.

- parameter of consumption or energy production of an element of the object (Fig. 4). Arrow 3 enters block 1.2

and the presence of values is checked

- energy supply and

- energy consumption and their relationship through the matrix

-

defining the internal structure of interaction

with the condition

... If the condition of block 1.2 is not met, then along arrow 4 through node 1.5

falls into block 1.3. In block 1.3, the matrix is found and redefined

... In block 1.3 such a matrix is generated

which will allow at least one parameter

resource income find the resource consumption parameter

... From block 1.3 on arrow 5 signal

goes to block 1.3.1 for verification. Block 1.3.1 checks fully characterized by parameters

object or not. If not, then

from block 1.3.1 along arrow 2 through node 01 it enters block 1.1. If so, follow arrow 6 through node 03

falls into block 1.4. If the check in block 1.2 is positive, then go along arrow 7 to node 03 and along arrow 8 to block 1.4. In block 1.4 where

divided into parameters / elements

directly involved in the exchange of energy with the external environment, namely, characterizing events that bring / consume the energy of the object, develop new qualities of the object, elements that act as conductors for the release of energy in the object or transfer it to a reserve. Further values

summed up by procedure

to the overall energy balance

:

... Value

through arrow 9 gets into block 1.6 for verification

... If the value

negative, then along arrow 10 it falls into node 1.5, from it along arrow 4.1 into block 1.3. If the value

positive, then through arrow 11 it enters block 1.7. In block 1.7, the identification of transient energy states

by transition matrix

to obtain a system of linear equations (SLE). Matrix

all possible transient states of the object in

limited by the structure of energy transfer inside the object and in contact with the external environment, also the transfer of energy to change the structure of the energy transfer in the future, the energy of separation into other objects, the energy of unification with other objects and the energy of preserving the structure.

The structure of the matrix without transient energy processes (Fig. 5), the structure of the matrix with transient energy processes (Fig. 6), the structure of the matrix with transient energy processes of the object (maternal) without taking into account the structure of the object of the separated object (daughter) (Fig. 7), the structure of the matrix with transient energy processes without taking into account the (parent) object, taking into account the structure of the object of the separated child object, which does not have its own processes of management and self-organization (Fig. 8). In this case, the processes of managing the child object in the structure of the parent object can be determined (Fig. 9). The structure of the matrix with transient energy processes of the child object, taking into account the change in the roles of the elements of the object for independent work (Fig. 10). The structure of the matrix with transient energy processes of the child object, taking into account the copying of the roles of the elements of the parent object for independent work (Fig. 11). The structure of the matrix of the parent object with processes oriented to the development of elements and the structure of the future child object (Fig. 12).

. Если условие блока 1.8 выполняется, то по стрелке 14 переходим в блок 1.10 через узел 1.9. Если условие блока 1.8 не выполняется, то по стрелке 13 через узел 1.19 и по стрелке 31 уходит сигнал на получение дополнительных параметров и объекте. В узле 1.9 добавляется метод воздействия (управления) выбранный для объекта и цели объекта. В блоке 1.10 вырабатываем контур управления (воздействия) пространство управления

- пространство управляющих воздействий на объект,

-

- вектор воздействий, структура управления

где

процедура устанавливающая соответствие матрицы структуры объекта

в структуру управления объектом

(Табл 1). Block 1.8 checks the resulting system of linear equations for the condition

... If the condition of block 1.8 is fulfilled, then along arrow 14 go to block 1.10 through node 1.9. If the condition of block 1.8 is not met, then along arrow 13, through node 1.19 and along arrow 31, a signal is sent to receive additional parameters and an object. In node 1.9, the method of action (control) is added, selected for the object and the purpose of the object. In block 1.10, we develop a control loop (influence) control space

- the space of control actions on the object,

-

- vector of impacts, management structure

Where

procedure for matching a matrix to an object structure

to the object management structure

(Table 1).

Energy vector direction Object element name in the syntax of the selected management standard (CS) The name of the element of the matrix A in the syntax of the selected control standard Name of the element of matrix B in the syntax of the selected control standard Name of the matrix element W in the syntax of the selected control standard

Plan

Fact

Admission CS element 1 Matr element. A 1 Matr element. B 1 Process 1.2

Consumption CS element 2 Matr element. A 2 Matr element. IN 2 Process 2.1

Income / Consumption CS element n Matr element. A n Matr element. In n Process n, n

(1):In block 1.10, we get the mathematical model of the object. According to the resulting model, the syntax of action (control), the goals of the object, a system is formed

(one):

передается в блок 1.11. В блоке 1.11 выполняем расчет семантических показателей (17), (18), (19), (20) как аналитическая функция (4), (4а)

, которая позволяет получать аналитические оценки состояния системы.Arrow 17 identifies the object as a system

passed to block 1.11. In block 1.11, we calculate the semantic indicators (17), (18), (19), (20) as an analytical function (4), (4а)

, which allows you to obtain analytical assessments of the state of the system.

рассчитываются на заданном временном интервале T и, как уже говорилось, характеризуют связность каждой функции в корреляционном графе. All four meanings

are calculated over a given time interval T and, as already mentioned, characterize the connectivity of each function in the correlation graph.

In addition, for the study of the system as a whole, the total ratings of the entire system (corresponding to the general connectivity of the correlation graph) are of interest.

(Фиг 13) с структурой матрицей и переходными процессами энергии (Фиг 6). Семантические показатели создания клона в 10 периоде (Фиг 14) и структура матрицы материнского объекта с процессами, ориентированными развитие элементов и структуры будущего дочернего объекта в 9 периоде (Фиг 12)., его отделение с 20 периода и присоединение в периоде 32 по структуре матрицы с переходными процессами энергии без учета (материнского) объекта с учетом структуры объекта отделившегося дочернего объекта, у которого нет своих процессов управления и самоорганизации (Фиг 8). Семантические показатели управления материнским объектом (Фиг 15) с структурой матрицы с переходными процессами энергии объекта (материнский) без учета структуры объекта отделившегося объекта (дочернего) (Фиг 7). Семантические показатели управления клоном (Фиг 16) с структурой матрицы с переходными процессами энергии объекта (материнский) без учета структуры материнского объекта (Фиг 7).An example of calculating planned and actual semantic indicators

(Fig. 13) with a matrix structure and energy transients (Fig. 6). Semantic indicators of clone creation in period 10 (Fig. 14) and the structure of the matrix of the parent object with processes oriented to the development of elements and structure of the future child object in period 9 (Fig. 12)., Its separation from the 20 period and joining in the period 32 according to the structure of the matrix with transient energy processes without taking into account the (parent) object, taking into account the structure of the object of the separated daughter object, which does not have its own processes of management and self-organization (Fig. 8). Semantic indicators of control of the parent object (Fig. 15) with the structure of the matrix with transient energy processes of the object (mother) without taking into account the structure of the object of the separated object (daughter) (Fig. 7). Semantic indicators of clone control (Fig. 16) with the structure of the matrix with transient energy processes of the object (mother) without taking into account the structure of the mother object (Fig. 7).

по семантическим показателям (Фиг 2) и (Фиг 3). Если выбираемые пороговые значения

не соблюдаются, то через стрелку 22 на узел 1.13. Из 1.13 по стрелке 21 на узел 1.15 и по стрелке 28 через узел 1.19 в алгоритм 1 для получения новых данных для идентификации объекта как системы. Параллельно из узла 1.13 по стрелке 24 в узел 1.16 и дальше по стрелке 20 в узел 1.5. Из узла 1.5 по стрелке 4.1 в блок 1.3. для уточнения матрицы

. Если условие симметричности выполняется, то по стрелке 23 система поступает в блок 1.14 для расчета остальных семантических показателей по правилам аналитической функций (4) - по прошлым значениям, (4а) - по будущим значениям:Next, the system goes along arrow 18 to block 1.12 for checking

by semantic indicators (Fig. 2) and (Fig. 3). If selectable thresholds

are not observed, then through arrow 22 to node 1.13. From 1.13 along arrow 21 to node 1.15 and along arrow 28 through node 1.19 to algorithm 1 to obtain new data to identify the object as a system. In parallel, from node 1.13 along arrow 24 to node 1.16 and further along arrow 20 to node 1.5. From node 1.5 along arrow 4.1 to block 1.3. to refine the matrix

... If the symmetry condition is satisfied, then along arrow 23 the system enters block 1.14 to calculate the remaining semantic indicators according to the rules of analytical functions (4) - according to past values, (4а) - according to future values:

1. Experience (foresight of the forecasting center) (25).

An example of the foresight of the regulatory functions of the system (Fig. 17). The example shows the maximum experience knowledge of 235 variables from 1 to 51 periods is not implemented.

Example table. 2

P t one 2 3 4 five 6 7 8 nine ten eleven 12 13 14 fifteen 16 17 18 19 20 n1 27 35 38 41 37 41 39 42 40 42 40 41 40 40 41 39 40 41 36 44 n2 34 34 18 38 38 37 38 37 3 33 34 24 235 235 235 235 235 235 235 235

Improving control from identifying the dimension of the object (Fig. 13) from period 12 to 14.

2. The sum of positive and negative values (26), (27).

Energy inflow / consumption by the system (Fig. 18).

3. Indicator of the structure of energy exchange between the elements of the system with the external environment (28).

The indicator shows that the elements of the system involved in attracting energy and consuming it in the current period, receive energy in the next (Fig. 19).

4. Index of the structure of energy exchange within the system (29).

The calculation was made for the system elements responsible for the matrix readjustment. It can be seen from the indicator that the system evolves sequentially (not abruptly) throughout the entire period, i.e. there is no repeating structure of attachments (Fig. 20).

5. Indicator of cycles of system operation (30).

Repetitive operating modes of the system are recorded (Fig. 21). Separately, you can analyze the repetitive modes of operation relative to the first period of operation (Fig. 22). Based on the analytical function (4) and (4a), it is possible to obtain repetitive modes of operation of the system of damped processes (Fig. 24) and increasing processes of the system (Fig. 23).

6. Indicator of the influence of environmental parameters on the operation of system elements (31)

The influence of the parameters of the external environment on the systems is recorded (Fig. 25). Based on the analytical function (4) and (4a), it is possible to obtain the influence of the parameters of the external environment, processes that tend to attenuate (Fig. 27) and on processes that tend to develop (Fig. 26). In the experiment, various modes were modeled that limit the activity of the system. For example, a mode without the influence of the external environment (Fig. 29) and with the influence of various modes of the external environment (Fig. 30)

7. The indicator of the identity of the influencing parameters of the external environment on the operation of system elements (31).

It is fixed that the parameters influencing the processes of the system influence from period to period in the same way (Fig. 28).

You can calculate any statistical indicators and apply methods of control theory, MSET (Multivariate State Estimation Technique), Kernel Regression, Kernel Regression, Support Vector Machine (SVM), Similarity Based Modeling (SBM) , neural networks, fuzzy logic, main components or boosting decision trees since the object is identified as a linear system.

The calculated values from block 1.14 along arrow 25 fall into block 1.17 to check the condition. If it is required to repeat the algorithm, then along arrow 27 to node 1.15 and along arrow 28 to algorithm 1. If not required, then along arrow 29 the data is transferred to node 15 and further along arrow 28 through node 1.19 along the arrow to algorithm 1. According to arrow 30 the algorithm is disabled.

From the existing level of technology, no objects have been identified that would contain a combination of the above essential features. This allows us to consider the claimed method as new. A set of features other than those of the aforementioned closest analogue is also unknown from the state of the art. This allows the claimed method to be considered as having an inventive step. The given examples of the implementation of the present invention serve only as illustrations and in no way limit the scope of patent claims defined by the claims.

The proposed method for identifying an object as a system, at the expense of semantic indicators, characterizes the processes of combining / separating objects as systems, characterizing them with a single metric, and also makes it possible to increase the efficiency and accuracy of identifying an object as a system, the efficiency and accuracy of control, and to improve the accuracy of identifying the goals of the system.

Example 2. The proposed method is implemented to identify and influence the management of an economic object under conditions of limited modes of its operation:

Masaev SN Guaranteed destruction of the activities of the enterprise of a resident of a special economic zone by sanctions / Twelfth International Conference "Management of Large-Scale Systems Development" (MLSD'2019): materials of the Twelfth Intern. conference, (Moscow, October 01-03, 2019). Moscow: IPU RAN, 2019, p. 232-235.

Masaev S. N. Destruction of the Resident Enterprise in the Special Economic Zone with Sanctions / 2019 Twelfth International Conference "Management of large-scale system development" (MLSD). IEEE. 2019. DOI: 10.1109 / MLSD.2019.8910997

Example 3. The proposed method is implemented to determine the foresight of the center for planning the activities of an object, system:

Masaev S.N. Determination of the planning horizon by the autocorrelation function in the process of managing an enterprise of a special economic zone / IX International Scientific and Technical Conference "Technologies for the Development of Information Systems (TRIS-2019): Proceedings of the Conference (Taganrog, September 6-13, 2019)." T. 1. Taganrog: SFedU, 2019. 52-59.

Graphic material

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Claims (3)

1. A method for identifying an object as a system by adding the space of observable variables when taking into account data characterizing the object contains a block for starting the operation of the observed parameters along the arrow one point zero point one, connected to the node zero one, the output of the node zero one along the arrow one point zero point two the information about the object observed by the elements of the observation matrix is an input to block one point one, from the external block one along the arrow one arrives at the node zero one signal with information about the observed parameters behind the object and along the arrow one point zero point two into the block one point one, block one point one observable data space translates into the space of parameters of consumption or resource / energy of an object element, along arrow three, parameters of income and consumption of resources / energy arrive in block one point two, and the presence of pairs of values of resource / energy inflow and resource / energy consumption is checked and their relationship through the structural matrix of the object, the signal that did not pass nd check for the presence of a pair for the income or resource / energy consumption parameter, along arrow four through node one point five and arrow four point one, the observed parameters fall into block one point three to supplement the elements of the structure of the object with a structural matrix and elements of the observation matrix, in block one point three, such a structural matrix is generated that will allow at least one parameter of resource / energy input to be compared with the second parameter of resource / energy consumption, and the elements of the observation matrix, along arrow five from block one point three, the signal of identified elements is sent for verification to block one point three point one, block one point three point one checks whether the object is fully characterized by elements of the structural matrix or not, an untested signal from the block one point three point one along arrow two through node zero one and arrow one point zero point two falls into block one point one, verified signal from block one point three points and one along arrow six through node zero three, then through arrow eight, the signal with the elements of the structural matrix enters block one point four to check the sufficiency of the resource / energy for the existence of the object, from block one point two go along arrow seven to node zero three and along the arrow eight in block one point four, where parameters interacting with the external environment are selected, the output of one point four of which along arrow nine falls into block one point six to check the conditions for attracting a resource / energy for the existence of an object at the moment of observing an object, an untested signal arrow ten enters node one point five, from it arrow four point one to block one point three the signal passed the test in block one point six through arrow eleven enters block one point seven, in block one point seven, identification is performed by the matrix of transition states energy at the time of observation, limited by the structural matrix of the object in contact with the external environment, exit from block one point seven along arrow twelve to the input of block one point eight, where the presence of a resource / energy at each point of observation and identification is checked, the signal that passed the test along arrow fourteen enters block one point ten through node one point nine , at node one point nine, the control method selected by the observer is added and / or is adjusted through the elements of the control structure matrix for the object / objects and the target of the object / objects in the direction of arrow fifteen, arriving along arrow sixteen in block one point ten to form a control space and control actions through the elements of the matrix of the control structure, where the matrix of the control structure is specified through the correspondence to the elements of the structural matrix of the corresponding control object, where the procedure that establishes the correspondence of the matrix of the elements of the object structure with the elements of the structure of the object control matrix, in the block one point ten we form the future states of the object through the parameters of receipt / consumption of resource / energy, taking into account the influence of the parameters of the external environment, according to the structural matrix of the observed object and the structural matrix of control, the observation matrix of the corresponding object is adjusted, according to the elements of the observation matrix, the achievement of the objectives of the research object is observed through the space of analytical estimates, in the block there is one point ten, we obtain an object identified as a system, the operation of which is characterized by a dynamic equation, an observation function during control that determines the parameters available for observation, a function for analyzing the operation of the system at previous moments in time, a function for analyzing the predicted values of the system's operation at future moments in time and with conditionally optimal control and a control action during operational control, the system regulator, which generates a control action depending on the deviation of the actual output parameters from the target values, along arrow seventeen, the object is identified cited as a system, it is transmitted to block one point eleven, in block one point eleven, the calculation of semantic indicators is performed, through the analytical function with the parameter of the depth of analysis, then the system along the arrow eighteen enters block one point twelve to check the requirements for the boundary of the semantic indicator and check the correctness structural matrix, which coincides with the dynamics of semantic indicators, a signal with values that did not pass the test condition is fed through arrow twenty-two to node one point thirteen, from node one point thirteen along arrow twenty-one to node one point fifteen and along arrow twenty-eight through the node one point nineteen and arrow thirty-one to the outer block one to obtain additional data to identify the object as a system, in parallel from node one point thirteen along arrow twenty four to node one point sixteen and further along arrow twenty to node one point five, from node one point five by arrow four point one in block one point three, to clarify the structural matrix, the signal that has passed the test for the conditions of boundaries and symmetry, at the node one point twelve and along arrow twenty-three enters the block one point fourteen for calculating, if necessary, mathematical operations and methods according to the rules of the analytical function, the object is identified as a linear system and other methods, the signal with control values from the block one point fourteen in the direction of the arrow twenty-five falls into the block one point seventeen to check the condition, the signal that did not pass the test, in the arrow twenty-seven to the node one point fifteen and along arrow twenty-eight through node one point nineteen and arrow thirty-one to outer block one, the signal that passed the test at one point eighteen along arrow twenty-nine is transmitted to node fifteen and further along arrow twenty-eight through node one point nineteen and arrow thirty-one to external block one, the signal passed the test y, is fed through arrow twenty-six to node one point eighteen and then to arrow twenty-nine to node one point fifteen and then through arrow twenty-eight to node one point nineteen and through arrow thirty-one to external block one, the signal at arrow thirty turns off the whole scheme. 2. The method according to claim 1, characterized in that at a given time by determining the parameters of the structure matrix of the observer of the phase space of the object, the observed object with a variable dimension by the number of observed and / or non-observed nonlinear parameters, the object is identified as a linear system. 3. The method according to claim 1, characterized in that the transition matrix characterizes all possible transition states of the object at the time of observation, limited by the structure of the energy transition inside the object and upon contact with the external environment, as well as the energy transition to change the structure of the energy transition in the future, by the separation energy to other objects, the energy of combining with other objects and the energy of preserving the structure of the object / objects.

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