|Article title||MODELING OF THE PROCESSES OF CREATION AND ESTIMATION FEASIBILITY INFORMATION AND CONTROL SYSTEMS MECHATRONIC COMPLEXES|
|Authors||A.E. Kolodenkova, V.V. Korobkin, A.P. Kuharenko|
|Section||SECTION III. DISTRIBUTED INFORMATION AND CONTROL SYSTEMS|
|Month, Year||10, 2015 @en|
|Index UDC||004.054; 519.81|
|Abstract||Discusses key concepts used in the simulation formation of the requirements to creation information and control systems (IСS) of mechatronic systems. It is noted that the formation of the requirements for the creation of IСS mechatronic systems is a difficult task, a quality solution that provides a framework and process control design ensures that after the completion of the system will fully meet the needs of the customer. Presented and described generalized scheme of the formation requirements for co-building IСS, allowing to see the relationship of each sub-steps (identification of the requirements, analysis of requirements, documentation requirements, validation of requirements and approval) of the process, and the impact environment on this process, which is especially important in the pre-trials. For the simulation of the formation of the requirements under uncertainty is proposed to use fuzzy time Petri net. To reduce the risks, fuss-penitent in the initial stages of the project life cycle to create IСS, held multi-criteria assessment of its feasibility. However, such an assessment is complicated by the presence of a large number criteria for defining the technical, financial, economic and commercial indicators developed by the project to create ICS. In connection with this problem of multi-criteria assessment of its feasibility of the project to date is relevant. Analysis of different approaches to the construction of models of multi-criteria evaluation of alternatives of projects under uncertainty showed that the parameters of the models often are interval values, which is associated with the use of methods of parametric identification of models with which you can often identify only the range of permissible values of parameters and with the existing range of opinions at receiving parameter values from the project executors. Where the source data for the establishment of ICS are not clear, it is proposed to apply the method of multi-criteria decision-making, based on the definition of the relationship between policies and their subsequent ranking under interval uncertainty.|
|Keywords||Information management systems; fuzzy Petri nets; fuzzy basic data; design alternatives reality estimation|
|References||1. Kalyaev I.A., Korobkin V.V., Mel'nik E.V., Khisamutdinov M.A. Metody i sredstva povysheniya bezopasnosti i sokrashcheniya vremeni operatsiy s yadernym toplivom na AES s reaktorom tipa VVER-1000 [The methods and means to improve safety and reduce the time of operation of nuclear fuel in nuclear power plants with VVER-1000]. Rostov-on-Don: Izd-vo YuFU, 2014, 208 p.
2. Lipaev V.V. Tekhniko-ekonomicheskoe obosnovanie proektov slozhnykh programmnykh sredstv [Feasibility study of complex software projects]. Moscow: SINTEG, 2004, 284 p.
3. Lipaev V.V. Programmnaya inzheneriya. Metodologicheskie osnovy: Uchebnik [Software Engineering. Methodological bases: Textbook]. Moscow: GU-VShE, TEIS. 2006, 603 p.
4. Korobkin V.V., Kolodenkova A.E. Odin iz podkhodov k otsenke bezopasnosti i riskov informatsionno-upravlyayushchikh sistem dlya atomnykh stantsiy [One approach to the estimation of no-hazard and risk information and control systems for nuclear power plants], XII Vserossiyskoe sove-shchanie po problemam upravleniya VSPU-2014: trudy [XII All-Russian conference on governance VSPU 2014: Works]. Available at: http://vspu2014.ipu.ru/node/8581.pdf (accessed 15 October 2015).
5. ISO/IEC 1207:2008 System and software engineering – Software life cycle processes. SC7 System and Software Engineering, 2008.
6. ISO/IEC/IEEE 15288:2015 Systems and software engineering - System life cycle processes. SC7 System and Software Engineering, 2015.
7. Avraham Shtub, Jonathan F. Bard, Shlomo Globerson. Project Management: Processes, Methodologies, and Economics (2nd Edition) (Prentice-Hall International Series in Industrial and Systems Engineering), 2004.
8. Lewis James P. Fundamentals of Project Management. American Management Association, 1997.
9. Principles of Project Management (Collected Handbooks from the Project Management Institute) Paperback – April 1, 1997. ISBN: 1880410303.
10. Omarov O.M. Teoriya vychislitel'nykh protsessov i struktur: Uchebnoe posobie [Theory of computing processes and structures. Tutorial]. Makhachkala: RIO DGTU, 2005, 268 p.
11. Leonenkov A.V. Nechetkoe modelirovanie v srede Matlab i fuzzyTECH [Fuzzy modeling in Matlab and fuzzyTECH]. St. Petersburg: BKhV-Peterburg, 2005, 736 p.
12. Shannon, Robert E. Systems simulation: the art and science. Englewood Cliffs, N.J.: Prentice-Hall, 1975.
13. Asarin E., Bournez O., Dang T. and Maler O. Reachability Analysis of Piecewise-Linear Dynamical Systems, in B. Krogh and N. Lynch (Eds.), Hybrid Systems: Computation and Control, 20-31, LNCS 1790, Springer, 2000.
14. Arsham H., Feuerverger, A., McLeish, D., Kreimer J. and Rubinstein R. Sensitivity analysis and the what-if problem in simulation analysis, Mathematical and Computer Modelling, 1989, No. 12 (1), pp. 193-219.
15. Tabucannon, Mario T. Multi Criteria Decision Making for Industry, Elsevier Publishers, 1988.
16. Li D.F. Fuzzy multiobjective many-Person decision makings and games, National Defense Industry Press, Beijing, 2003.
17. Deng J.L. Control problems of grey systems, Systems and Controls Letters, 1982, No. 5, pp. 288-294.
18. Zhang J., Wu D., Olson D. The method of grey related analysis to multiple attribute decision making problems with interval numbers, Mathematical and Computer Modelling, 2005, pp. 991-998.
19. Xu ZS. Projection method for uncertain multi-attribute decision making with preference information on alternatives // Int. J. Info. Technol. Decis. Making, 2004, No. 3 (3), pp. 429-434.
20. Xu G., Yang Y.–P., Lu S.–Y., Li L. and X. Song. Comprehensive Evaluation of Coal-fired Power Plants Based on Grey Relational Analysis and Analytic Hierarchy Process, Energy Policy, 2011, Vol. 5, pp. 39.