Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation
Controlling a complex dynamic object in real time and satisfying multiple criteria involves constant dealing with state deviations from the constructed plan, caused by external disturbances of a stochastic nature, and the lack of knowledge about the controlled object in the process of building the p...
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doaj-2880e3c5986149218ea368413e0c3db92020-11-24T21:31:45ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372019-04-0185424608612Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance CompensationAndrey Gnidenko0Vladislav Sobolevsky1Valerity Zakharov2St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Saint Petersburg, RussiaSt. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Saint Petersburg, RussiaSt. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Saint Petersburg, RussiaControlling a complex dynamic object in real time and satisfying multiple criteria involves constant dealing with state deviations from the constructed plan, caused by external disturbances of a stochastic nature, and the lack of knowledge about the controlled object in the process of building the plan. The present paper suggests models and algorithms for compensating such deviations in relation to the control of individual trains within the framework of the developed multi- level multi-model complex designed for group planning and coordination of trains within a single logistics network. Another covered aspect is the algorithm of parametric adaptation, involving adjustment of model parameters and improvement of planning accuracy.https://fruct.org/publications/abstract24/files/Gni.pdf multi-criteria optimizationoptimal controlsolution constraintscomplex planningproactive controlparametric adaptation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andrey Gnidenko Vladislav Sobolevsky Valerity Zakharov |
spellingShingle |
Andrey Gnidenko Vladislav Sobolevsky Valerity Zakharov Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation Proceedings of the XXth Conference of Open Innovations Association FRUCT multi-criteria optimization optimal control solution constraints complex planning proactive control parametric adaptation |
author_facet |
Andrey Gnidenko Vladislav Sobolevsky Valerity Zakharov |
author_sort |
Andrey Gnidenko |
title |
Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation |
title_short |
Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation |
title_full |
Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation |
title_fullStr |
Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation |
title_full_unstemmed |
Methods and Algorithms of Proactive control of Complex Dynamic Objects with Disturbance Compensation |
title_sort |
methods and algorithms of proactive control of complex dynamic objects with disturbance compensation |
publisher |
FRUCT |
series |
Proceedings of the XXth Conference of Open Innovations Association FRUCT |
issn |
2305-7254 2343-0737 |
publishDate |
2019-04-01 |
description |
Controlling a complex dynamic object in real time and satisfying multiple criteria involves constant dealing with state deviations from the constructed plan, caused by external disturbances of a stochastic nature, and the lack of knowledge about the controlled object in the process of building the plan. The present paper suggests models and algorithms for compensating such deviations in relation to the control of individual trains within the framework of the developed multi- level multi-model complex designed for group planning and coordination of trains within a single logistics network. Another covered aspect is the algorithm of parametric adaptation, involving adjustment of model parameters and improvement of planning accuracy. |
topic |
multi-criteria optimization optimal control solution constraints complex planning proactive control parametric adaptation |
url |
https://fruct.org/publications/abstract24/files/Gni.pdf
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work_keys_str_mv |
AT andreygnidenko methodsandalgorithmsofproactivecontrolofcomplexdynamicobjectswithdisturbancecompensation AT vladislavsobolevsky methodsandalgorithmsofproactivecontrolofcomplexdynamicobjectswithdisturbancecompensation AT valerityzakharov methodsandalgorithmsofproactivecontrolofcomplexdynamicobjectswithdisturbancecompensation |
_version_ |
1725959900713975808 |