At present, there are many problems in the research on building system regulation and control, such as conflicting scheduling methods and underutilization of demand-side response resources, which will hinder the stabl...
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The research is devoted to the methods of state-dependent coefficient (SDC) for solving nonlinear optimal controlproblems. An important stage in the application of SDС methods is the parameterization (or even say fa...
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The article discusses the features of designing and optimizing non-contact DC motors with fractional multi-section windings as part of an electric drive of a rotary-blade system with a gearbox. An important problem at...
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This article discusses the main types of models of complex processes and systems, which are represented by structures based on graphs - graphs, fuzzy cognitive maps, fuzzy temporal graphs. Particular attention is paid...
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This paper introduces CoGoV: a new Matlab-based toolbox for the simulation of Command Governor supervision strategies applied to distributed motion planning problems for multivehicle systems. CoGoV is an open-source a...
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ISBN:
(纸本)9781713872344
This paper introduces CoGoV: a new Matlab-based toolbox for the simulation of Command Governor supervision strategies applied to distributed motion planning problems for multivehicle systems. CoGoV is an open-source and object-oriented software and contains several classes for modeling unmanned vehicles, designing control strategies and solving optimization problems for achieving prescribed tasks in complex simulation scenarios. Because of its modular structure, it can be used to supervise many kinds of autonomous vehicles in marine, terrestrial and aerial domains. Throughout the paper, the benefits of the toolbox are presented by means of simulations involving the supervision and coordination of autonomous marine surface vehicles.
Distributed healthcare systems require strong security and privacy measures because Electronic Health Records (EHRs) are highly sensitive and regulations are strict. The advancing technologies increase the healthcare ...
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With the rapid development of robotics and automation, online trajectory planning faces problems such as poor adaptability to dynamic environments and low computational efficiency. This study aims to propose a collabo...
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The problems of the non-stationary complex heat transfer have been considered in the work. An optimization algorithm based on machine learning methods has been proposed. The algorithm uses a neural network trained on ...
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Human-driven vehicles (HVs) exhibit complex and diverse behaviors. Accurately modeling such behavior is crucial for validating Robot Vehicles (RVs) in simulation and realizing the potential of mixed traffic control. H...
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In addition to process control at the equipment level, the identification of systemic hazards and the realization of process safety are also part of the operational problems of complexsystems. To improve the effectiv...
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ISBN:
(纸本)9781713872344
In addition to process control at the equipment level, the identification of systemic hazards and the realization of process safety are also part of the operational problems of complexsystems. To improve the effectiveness of hazard identification based on the Multilevel Flow Modelling(MFM) models, this paper proposes that a hazard-oriented knowledge representation can represent more hazards than previous models used for online operational decision support in terms of latent intention, chemical, and physical hazard properties of materials and effects of multiple conditions in combination. Thus, the scope of application of the MFM model is extended from online operational decision support to hazard identification, and the application phase of the model is extended from the operational phase to the design phase. Moreover, the results are demonstrated by a Minxo process modeling and compared with its Hazard and Operability study(HAZOP) report results, and the representation rate of hazard of the MFM model incorporating hazard-oriented knowledge is improved, showing great potential for further optimization of the MFM-assisted HAZOP study. Copyright (c) 2023 The Authors.
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