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TDSHKEIMT DAVLAT TRANSPORT UNIVEHSITETI
Ташкентский гссударстмнчый транспортный университет
"Актуальные вопросы развития инновационно-информационных технологий на транспорте" АВРИИТТ-2021 1-Республиканская научно-техническая конференция (Ташкент, 24-25 ноября 2021 года)
INFORMATION ANALYSIS OF THE EXPERT SYSTEM OF AUTOMATIC TRAIN CONTROL
Ravshan ALIEV,
Professor, Department of Information Systems and Technologies, Tashkent State Transport University, Tashkent, Uzbekistan E-mail: alievravshan [email protected] Kamoliddin TASHMETOV, Senior teacher, Department of Information Systems and Technologies, Tashkent State Transport University Marat ALIEV,
Professor, Department of Information Systems and Technologies, Tashkent State Transport University Ezozbek TOKHIROV,
Senior teacher, Department of Information Systems and Technologies, Tashkent State Transport University E-mail: [email protected] DOI: https://doi.org/10.47689/978-9943-7818-0-1-pp23-25
Annotation: The expert system for automatic control of train traffic belongs to the class of information systems of automation and tele mechanics. The model, which reflects the informational links between the main goal and the characteristics of the automatic train control system, is informational. It can be used to conduct a qualitative analysis and synthesis of the system.
Key words: expert system, information links, automatic control of train traffic, train, throughput.
MAIN PART
In order to build an information model of the system, it is necessary, first of all, to formulate the main target tasks of the system and to determine the amount of information that needs to be processed when solving the main target tasks [1].
The main task of the expert system for automatic control of train movement is automatic control [2] behind the running train B2 to the train in front. In this case, the necessary throughput must be ensured with complete traffic safety [3]. To do this, in general, you need to have the following information in the system: characteristics of the movement of the ahead running train B±: actual speed vx, location s±, braking performance K±, length L±; characteristics of movement behind the running train B2; actual speed v2, location S2, braking performance K2; characteristics of the path of movement: track profile i, track plan R; own operational and technical characteristics of the Q system: performance and errors.
Some of these characteristics are a priori known, have the nature of parameters for automatic control and can be stored in the system memory even before the start of the automatic traffic control process (breaking characteristics, train lengths, track profiles and plans, system characteristics) [4, 5, 6]. Some of the characteristics are a
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TQfiHKENl DAVLAT TftAN SPORT UN IV ER SITdl
Ташкентский государственный транспортный университет
"Актуальные вопросы развития инновационно-информационных технологий на транспорте" АВРИИТТ-2021 I-Республиканская научно-техническая конференция (Ташкент, 24-25 ноября 2021 года)
priori unknown, depend on the movement, have a variable character for automatic control of movement and must be entered into the control device of the expert system during operation (speed and location of trains).
The control device of the automatic train control system processes the information v1, v2, 51, S2 received from the controlled objects (trains B1 and B2), taking into account the information stored in the memory of the system and issues the train B2 an order for the programmed speed v2pr and some additional information that makes it easier for the driver driving train B2 (distance between B1 and B2, actual train speed v2, profile i and track plan R).
Thus, the information model of the expert system for automatic control of train traffic can be represented in the form shown in Fig. 1.
In this information model, train S2means any train Bt behind it, and train B1 means any train Bt-1. in front.
The direction, nature and volume of information flows indicated on the model are necessary and sufficient for the most complex and high-quality of the known cases of automatic regulation of train traffic, therefore this model is generalized. Information models of other cases (systems) of automatic control of train traffic are special cases of the given generalizations of the model and are obtained from the latter by deleting certain connections (information flows) or characteristics (nature or volume of information). Therefore, the analysis performed on the generalized information model is a generalized analysis of the automatic control of train traffic.
Fig.1. Information model of the expert system for automatic control
of train traffic
CONCLUSION
The generalized model can be reduced to a form that is more convenient for analysis, as well as its concepts can be expanded. To do this, let us focus on the fact
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TDSHKEIMT DAVLAT TRANSPORT UNItfERSlTETI
Ташкентский гссударстоенчый транспортный университет
"Актуальные вопросы развития инновационно-информационных технологий на транспорте" АВРИИТТ-2021 ^Республиканская научно-техническая конференция (Ташкент, 24-25 ноября 2021 года)
that the main task of the automatic control system for train traffic is to automatically control the movement behind the B2 train going on to the B1 train in front, ensuring the required throughput with complete traffic safety. From this it can be seen that the main task is to automatically regulate the movement behind the running train B2. The ahead train B1 acts as a hindrance to the movement behind the train B2, disturbing the movement of the train B2. This interference requires a corresponding change in the characteristics of movement (v2, S2) behind the running train B2, when changing the characteristics (v1, 51) of the train B1 in front.
REFERENCES:
1. Ravshan Aliev 2021 A Rail line model with distributed parameters of track circuit IOP Conf. Series: Materials Science and Engineering 1152 (2021) 012018.
2. Aliev R.M., Aliev M.M. (2020) Methods for calculating the coefficients of the rail fourpole of sensors control tonal frequency. Chemical Technology, Control and Management: Vol. 2020: Iss. 5, Article 13. - PP. 68-72.
3. Aliev Marat, Aliev Ravshan, Tokhirov Ezozbek, Nurmuhamedov Tolaniddin (2019) Four-Pole Rail Coefficients of the Jointless Track Circuit in The Presence of One of the Ends Track Circuit Insulating Joints. Chemical Technology, Control and Management: Vol. 2019: Iss. 4, Article 6. - PP. 89-92.
4. Nadya Alinda Rahmi1, Gunadi Widi Nurcahyo Sistem Pakar dalam Membandingkan Metode Forward Chaining dengan Certainty Factor untuk Mengidentifikasi Jenis Kulit Wajah Jurnal Sistim Informasi dan Teknologi Vol. 3 No. 4 (2021) - PP. 257-262.
5. Tashmetov Timur, Tashmetov Kamoliddin, Aliev Ravshan, Rasulmuhamedov Muhamadaziz (2020) Fuzzy information and expert systems for analysis of failure of automatic and telemechanic systems on railway transport. Chemical Technology, Control and Management: Vol. 2020: Iss. 5, Article 29. - PP. 168-171.
6. Aliev R., Aliev M., Tokhirov E. Model microprocessor device of four-wire scheme of the direction change. German International Journal of Modern Science No11, 2021. - PP. 30-32.
