Complex Simulation of Automated Control System of Navigation Spacecraft Operation

Sokolov, Boris; Yusupov, Rafael

doi:10.1615/jautomatinfscien.v34.i10.30

Cited by 9 publications

(6 citation statements)

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“…The operations in the black and white areas are not being considered at the given points of time, and, therefore, will not influence the assignment matrix size. This is the principal advantage of the proposed dynamic decomposition as compared to mathematical programming and combinatorial optimisation theory Sokolov 1985, 1987;Sokolov and Yusupov 2002;Ivanov andSokolov 2010, 2012;Ivanov, Sokolov, and Dolgui 2012).…”

Section: Constraintsmentioning

confidence: 99%

“…For job shop scheduling, precedence relations exist. The studies by Sokolov (1985, 1987), Sokolov and Yusupov (2002) resolved the aforementioned problems with multiple criteria, bans on execution interruptions and non-stationarity for large-scale scheduling problem. The studies by Ivanov andSokolov (2013a, 2013b), Ivanov et al (2016a), Ivanov, Dolgui, and Sokolov (2016b), Ivanov et al (2016c) developed a special form of hybrid terminal-logical constraints that allows the application of maximum principle-based optimal control models to job and flow shop to the supply chain scheduling.…”

Section: Constraintsmentioning

confidence: 99%

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Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications

Dolgui

Ivanov

Sethi

et al. 2018

International Journal of Production Research

235

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This paper presents a survey on the applications of optimal control to scheduling in production, supply chain and Industry 4.0 systems with a focus on the deterministic maximum principle. The first objective is to derive major contributions, application areas, limitations, as well as research and application recommendations for the future research. The second objective is to explain control engineering models in terms of industrial engineering and production management. To achieve these objectives, optimal control models, qualitative methods of performance analysis and computational methods for optimal control are considered. We provide a brief historic overview and clarify major mathematical fundamentals whereby the control engineering terms are brought into correspondence with industrial engineering and management. The survey allows the grouping of models with only terminal constraints with application to master production scheduling, models with hybrid terminal-logical constraints with applications to short term job and flow shop scheduling, and hybrid structural-terminal-logical constraints with applications to customised assembly systems such as Industry 4.0. Computational algorithms in state, control and adjoint variable spaces are discussed.

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Section: Constraintsmentioning

confidence: 99%

Section: Constraintsmentioning

confidence: 99%

Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications

Dolgui

Ivanov

Sethi

et al. 2018

International Journal of Production Research

235

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“…However, human practical experience gives enough evidence for these specific features of a model to be quite acceptable for the solution of problems that subjects have to deal with. Applying the principle of accuracies balance, it is always possible to reach a compromise between how detailed the description of an original object is and the pragmatic value of a designed model (Peschel 1981;Sethi and Thompson 2006;Sokolov and Yusupov 2004;Sokolov and Yusupov 2002). The analysis of definitions given above shows that for modeling of different types of CO, both natural and artificial, it is reasonable to define the following basic elements and relations that characterize a certain process: firstly, a subject or subjects…”

Section: Generalized Description Of the Problems Of Subject-object Momentioning

confidence: 99%

“…It is required to perform multicriteria dynamic structural-functional synthesis of both multiple-model complex itself (based on the purposes of modeling set by a subject and indicators of quality of modeling that are used) and a corresponding technology of system modeling of a situation in progress, so that for each given scenario of changing disturbing actions on a situation in progress the most preferable transition from its current to a required structural state is reached. Let us provide a formalization of these tasks with the use of the theory of control of structural dynamics of CO, which is being developed by the authors Okhtilev et al 2006;Sokolov and Yusupov 2002). For a constructive description of relations between above listed subjects and objects which are basic components of a situation in progress we will introduce a dynamic system alternative multigraph (DSAM) with transformable structures that looks the following way:…”

Section: Generalized Description Of the Problems Of Subject-object Momentioning

confidence: 99%

Quality Evaluation Of Models And Polymodel Complexes: Subject-Object Approach

Sokolov¹,

Sobolevsky²,

Mikoni³

et al. 2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

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New approach of models and multiple-models quality evaluation is proposed. This approachis based on twofold ideas. First, when selecting an object for modeling it is reasonable to select not a really existing (designed or abstract) object but a situation in progress, that includes the objects and the subjects of the modeling (people responsible for making decisions (DM), people responsible for the substantiation of a decision (solution), experts, and people responsible for the implementation of solutions. Second, the process of modeling is here assumed as a control process of developing situation under uncertain conditions, caused by absence of information needed for forming the substantiated decisions. The descriptive and formal statement of quality control of models and multiplemodel complexesare interpreted as problems of structural-functional synthesis of a model (a multiplemodel complex) and also, selection of optimal programs of control and regulation of structural dynamics of a situation in progress (quality control of models and multiple-model complexes).The example of solving the task of poly-model finding distances from a vertex to all other vertices of a graph is proposed.

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“…Many complex technical objects (CTO) are remotely controlled [1,2,3]. Operators (dispatchers) receive information about current CTO states in a form of telemetry.…”

Section: Introductionmentioning

confidence: 99%

Information and Telecommunication Intellectual Monitoring Technology and System for Complex Technical Objects under Dynamic Conditions in Real Time

Okhtilev¹,

Sokolov²,

Vinel³

et al. 2009

Proceedings of the International Workshop on Networked Embedded and Control System Technologies: European and Russian R&D C

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The aim of the investigation is to develop methods, models and algorithms of synthesis and intellectualization of monitoring technology and system oriented to concurrent on-line user software assurance for all sorts of measuring information specifying states of complex technical objects under dynamic conditions in real time. This aim should be achieved by here suggested artificial intelligent information technology. The basis of this artificial intelligent information technology is flow computing models exploitable by state hipping (constraint programming) in real time and in territorially distributed computing network. At the same time each network node represents artificial intelligent agent. Furthermore, the problem of efficient information transmission between the complex technical objects and monitoring systems by means of contemporary wireless technologies is considered. * * This work is supported by the Russian Foundation for Basic Research projects № 07-07-00169, 08-08-00403, 09-07-00066, Russian Humanitarian Scientific Foundation 09-01-12105, Department of Nanotechnologies and Information Technologies-Project 2.3. Alexey Vinel acknowledges the support of Alexander von Humboldt Foundation.

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Complex Simulation of Automated Control System of Navigation Spacecraft Operation

Cited by 9 publications

References 0 publications

Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications

Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications

Quality Evaluation Of Models And Polymodel Complexes: Subject-Object Approach

Information and Telecommunication Intellectual Monitoring Technology and System for Complex Technical Objects under Dynamic Conditions in Real Time

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