UDC 303.732.4
1 National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine,
vkhilenko@ukr.net
|
|
ALGORITHM FOR DECOMPOSITION CONTROL AND PREDICTION
OF TRAJECTORIES OF NONLINEAR STOCHASTIC SYSTEMS UNDER
DIFFERENT-SPEED PROCESSES IN THEIR DYNAMICS
Abstract. The author proposes a decompositional algorithm for predicting the trajectories of nonlinear stochastic systems whose dynamics contain subprocesses significantly different in speed. The algorithm is focused on reducing the time to obtain predictive results for substantially nonlinear objects and systems, when calculations based on their complete mathematical models are associated with a large amount of computation and the complexity of temporary adjustment of parameters.
Keywords: nonlinear stochastic systems, mathematical modeling and forecasting of dynamics, control of dynamic systems, decomposition of models.
FULL TEXT
REFERENCES
- Kutz J., Brunton S., Brunton B., Proctor J. Dynamic mode decomposition: Data-Driven Modeling of Complex Systems. SIAM. Philadelphia, 2016. 250 p.
- Jones B., Ryan M. The utility of decomposition as systems engineering tool. Conference: Systems Engineering. Test and Evaluation Conference SETE-2012. Canberra, 2012.
- Widrow B., Stearns S. Adaptive signal processing [Russian translation]. Moscow: Radio i svyaz', 1989. 388 p.
- Khilenko V.V., Strzelecki R., Kotuliak I. Solving the problem of dynamic adaptability of artificial intelligence systems that control dynamic technical objects. Cybernetics and Systems Analysis. 2018. Vol. 54, N 6. P. 867–873.
- Akhmetov B., Lakhno V., Malyukov V., Zhumadilova M., Kartbayev T. Decision support system about investments in smart сity in conditions of incomplete information. International Journal of Civil Engineering and Technology. 2019. Vol. 10, Iss. 2. P. 661–670.
- Ivanov A.O. Theory of automatic control [in Russian]. Dnepropetrovsk: National Mining University, 2003. 250 p.
- Khilenko V. Order reduction methods and adequate simplification of the models with uncertain coefficients. Cybernetics and Systems Analysis. 1998. Vol. 34, N 3. P. 458–461.
- Afanasiev V.N. Stochastic systems. Estimates and control [in Russian]. Moscow: LENAND, 2018. 152 p.
- Grishchenko A.Z., Khilenko V.V. Determining the number of fast and slow components in decomposition of arbitrarily large linear dynamical models. Cybernetics and Systems Analysis. 1991. Vol. 27, N 6. P. 795–801.
- Poston T., Stuart I. Catastrophe theory and its applications [Russian translation]. Moscow: Mir, 1980. 607 p.
- Sanns W. Catastrophe theory with mathematica: A geometric approach. Germany: DAV, 2000. 175 p.
- Khilenko V., Butko I., Ternavsjka V. Application of decomposition methods for solving the problems of processing of geoinformation systems. Monitoring 2019 Conference — Monitoring of Geological Processes and Ecological Condition of the Environment, 2019.