MATHEMATICAL MODEL OF THE SYSTEM OF AUTOMATIC OBJECT STATE CONTROL BY THE VECTOR OF SYSTEM PARAMETERS
10.33815/2313-4763.2021.2.25.092-100
Abstract
The article considers a promising method of diagnostics and automatic control by the vector of parameters to solve the problem of increasing the efficiency of operation of the ship's emergency warning system (APS). In the mathematical model of the system for diagnosing the state of ship systems, an algorithm is implemented that allows for automatic monitoring and forecasting of the state of the ship and its systems.
The implementation of additional feedback in the form of a controller in the control system algorithm allows not only to accumulate information about the decisions made, the results obtained, and fault signals, but also ensures the comparability of the results based on diagnostic information.
Such an implementation of the asymptotic state observer makes it possible to quickly eliminate the error associated with the initial conditions or uncontrolled perturbations. The implementation of this method is quite simple in both analog and digital algorithms. The article shows the implementation of the algorithm by the Runge-Kutta method of the first order. For the asymptotic convergence of the estimation error to zero, the observer matrix is chosen arbitrarily.
The article shows that in order to predict the state of an object, it is necessary to estimate the rate of change of the vector of object parameters, but this is quite difficult to do by estimating the state vector.
The paper also shows that it is possible to evaluate the dynamics by an equation in the state space of parameters with a matrix, however, in this case, it is necessary to single out the area in which the state vector determines a positive forecast of the system's performance.
The use of a decision support system with feedback (DSS, eng. DSS - decision support system) in automatic control tasks, as an intelligent system with an observer along the state vector, allows you to receive information about the state of ship systems in real time and predict their future state.
References
2. KONSBERG. Kongsberg K-Chief 500/600 Marine Automation System Installation Manual /311956 / F March 2013 © Kongsberg Maritime AS.
3. Zgurovskiyj, M. Z. Sistemnihyj analiz: problemih, metodologiya prilozheniya / M. Z. Zgurovskiyj, N. D. Pankratova. K.: Naukova dumka, 2005. – 742.
4. Akimov V. A. Nadezhnostj tekhnicheskikh sistem i tekhnogennihyj risk
/ V. A. Akimov, V. L. Lapin, V. M. Popov. M.: Delovoyj ehkspress, 2002. – 367 s.
5. Portnyagin N. N., Pyukke G. A. Teoriya, metodih i ehksperimentih resheniya zadach diagnostiki sudovihkh ehlektricheskikh sredstv avtomatizacii. – SPb.: Sudostroenie, 2004. 162 s.
6. Tikhonov A. N. Differencialjnihe uravneniya 4-e izd. A.N. Tikhonov, Vasiljeva A. B. Sveshnikov A. G. M.: Fizmatlit. 2002. 232 s.
7. Vihchuzhanin V. V. Informatizaciya distancionnogo diagnostirovaniya sostoyaniya slozhnihkh tekhnicheskikh sistem [Tekst] / V. V. Vihchuzhanin, S. N. Konovalov // Informatika i matematicheskie metodih v modelirovanii, 2016. – Tom 6, №1. – S. 303–311.
8. Sergiy Rozhkov, Kostyantyn Kondrashov, Oksana Tereshchenkova, Maryna Falenkova. Informational expert system for minimizing the time in searching of ship electrical equipment failures. CEUR-WS.org/Vol–2845 – Information technology and interactions (IT&I 2020), р. 418–426.
9. Sergiy Rozhkov, Kostyantyn Kondrashov, Oksana Tereshchenkova, Maryna Falenkova. Informational Expert System for Minimizing the Time in Searching of Ship Electrical Equipment Failures Proceedings of the 7th International Conference "Information Technology and Interactions" (IT&I-2020). Workshops Proceedings Kyiv, Ukraine, December 02-03, 2020. P. 170–180. http://ceur-ws.org/Vol-2845/Paper_17.pdf.
10. Kashtalyan P. V., Rozhkov S. O. Mathematical and information provisions of bridge team training control systems // Electronics and Control Systems, 2019. No2(06). P. 61–69. (ISSN 1990–5548) doi: 10.18372/1990-5548.60.13816.
