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Dembia, Christopher L., Nicholas A. Bianco, Antoine Falisse, Jennifer L. Hicks y Scott L. Delp. "OpenSim Moco: Musculoskeletal optimal control". PLOS Computational Biology 16, n.º 12 (28 de diciembre de 2020): e1008493. http://dx.doi.org/10.1371/journal.pcbi.1008493.
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Musculoskeletal simulations are used in many different applications, ranging from the design of wearable robots that interact with humans to the analysis of patients with impaired movement. Here, we introduce OpenSim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation. Moco frees researchers from implementing direct collocation themselves—which typically requires extensive technical expertise—and allows them to focus on their scientific questions. The software can handle a wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which enable modeling of kinematic loops (e.g., cycling models) and complex anatomy (e.g., patellar motion). To show the abilities of Moco, we first solved for muscle activity that produced an observed walking motion while minimizing squared muscle excitations and knee joint loading. Next, we predicted how muscle weakness may cause deviations from a normal walking motion. Lastly, we predicted a squat-to-stand motion and optimized the stiffness of an assistive device placed at the knee. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand the movement of humans and other animals.
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Никитин, Д. А., Д. Е. Цыбин, А. М. Хафизов, С. А. Мишин, А. Ф. Тайчинов y Э. М. Сафин. "ADAPTIVE VIRTUAL ANALYZER IN ADVANCED PROCESS CONTROL". Южно-Сибирский научный вестник, n.º 2(36) (30 de abril de 2021): 149–57. http://dx.doi.org/10.25699/sssb.2021.36.2.004.
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В данной статье рассматривается разработка адаптивного виртуальногоанализаторов (ВА) показателей качества для проекта системы усовершенствованного управления Advanced Process Control (СУУТП, далее «APC»). Построение моделей ВА произведено с помощью регрессионных методов по параметрам, влияющих в наибольшей степени на выброс монооксида углерода, содержание кислорода в дымовых газах, температуры змеевика. В качестве метода оценки моделей предложен векторный критерий, определяющий значения ширины окна ВА с наиболее оптимальными значениями коэффициента детерминации и среднеквадратичной ошибкой. Интеграция моделей ВА в систему управления обеспечивает оптимизацию параметров работы с целью улучшения качественных и количественных показателей производимой продукции, а также позволяет существенно снизить затраты в области оборудования поточной аналитики. This article discusses the development of adaptive virtual analyzers (VA) of quality indicators for the project of the advanced control system Advanced Process Control (SUUTP, hereinafter referred to as "APC"). The construction of VA models was carried out using regression methods for the parameters that affect to the greatest extent the emission of carbon monoxide, the oxygen content in the flue gases, and the coil temperature. As a method for evaluating models, a vector criterion is proposed that determines the values of the VA window width with the most optimal values of the determination coefficient and the root-mean-square error. Integration of VA models into the control system ensures optimization of operating parameters in order to improve the qualitative and quantitative indicators of manufactured products, as well as significantly reduce costs in the field of flow analytics equipment.
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Feng, Jinfeng. "Optimal Control Strategy Model of Marketing Management Based on Consumer Psychology". Mathematical Problems in Engineering 2022 (3 de octubre de 2022): 1–10. http://dx.doi.org/10.1155/2022/8689244.
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This paper uses an optimal control strategy approach to conduct an in-depth study and analysis of consumer psychology and to design marketing management in this way. The process simulation enhances consumer participation in virtual CSR co-creation by enhancing task meaning perceptions, and the outcome simulation weakens consumer participation in virtual CSR co-creation by decreasing task meaning perceptions. Second, the proximity of the target distance positively moderates the relationship between psychological stimulation and task meaning perceptions, with process simulation having a stronger effect on task meaning perceptions at closer target distances than at longer target distances; the proximity of the target distance positively moderates the relationship between psychological simulation and consumer engagement in virtual CSR co-creation, with process simulation having a stronger effect on consumer engagement in virtual CSR co-creation at closer target distances than at longer target distances. The effect of simulation on consumers’ participation in virtual CSR co-creation is stronger at a closer target distance than at a farther target distance. A multi-input and multioutput block diagram structure is proposed in the frequency domain to describe the characteristics of the multisubject system with transfer functions. Males and females accounted for 58.6% and 41.4% of the total sample population, respectively. The entire multisubject system is decomposed according to matrix theory, and the consistency problem of the multisubject system is converted into the stability problem of multiple subsystems. The global stability domain of the distributed PID controller is obtained by finding the stability domain of the PID controller for each subsystem after decomposition and taking the intersection set. The product green preferences of consumers are incorporated into the demand model, and the correlation between the inventory strategy of products, green inputs, and the manufacturer’s confident preferences is investigated. The article considers two models of centralized inventory management and decentralized inventory management for manufacturers and conducts a cross-sectional comparison. The article finds through numerical experiments that the manufacturer’s assertive behavior in most cases makes its gains suffer but is often beneficial for the interests of retailers, overall supply chain efficiency, and environmental friendliness.
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Zeng, Jinhui, Yao Rao, Zheng Lan, Dong He, Fan Xiao y Bei Liu. "Multi-Objective Unified Optimal Control Strategy for DAB Converters with Triple-Phase-Shift Control". Energies 14, n.º 20 (9 de octubre de 2021): 6444. http://dx.doi.org/10.3390/en14206444.
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To solve the problems of large current stress, difficult soft-switching of all switches, and slow dynamic response of dual active bridge converters, a multi-objective unified optimal control strategy based on triple-phase-shift control was proposed. The forward power flow global modes of triple-phase-shift control were analyzed, and three high-efficiency modes were selected to establish the analytical models of current stress and soft-switching. Combined with these models, the optimal solutions in different modes were derived by using the cost function-optimization equation to overcome the limitation of the Lagrange multiplier method, such that the DAB converter achieved the minimum current stress, and all switches operated in the soft-switching state over the entire power range. At the same time, the virtual power component was introduced in the phase-shift ratio combination, which improved the dynamic response of output voltage under the input voltage or load steps changed by power control. The theoretical analysis and experimental results show that the proposed control strategy can optimize the performance of the DAB converter from three aspects, such as current stress, soft-switching, and dynamic response, which achieves multi-objective optimization of the steady-state and dynamic performance of DAB converters.
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Kuutti, Sampo, Richard Bowden y Saber Fallah. "Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages". Sensors 21, n.º 6 (13 de marzo de 2021): 2032. http://dx.doi.org/10.3390/s21062032.
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The use of neural networks and reinforcement learning has become increasingly popular in autonomous vehicle control. However, the opaqueness of the resulting control policies presents a significant barrier to deploying neural network-based control in autonomous vehicles. In this paper, we present a reinforcement learning based approach to autonomous vehicle longitudinal control, where the rule-based safety cages provide enhanced safety for the vehicle as well as weak supervision to the reinforcement learning agent. By guiding the agent to meaningful states and actions, this weak supervision improves the convergence during training and enhances the safety of the final trained policy. This rule-based supervisory controller has the further advantage of being fully interpretable, thereby enabling traditional validation and verification approaches to ensure the safety of the vehicle. We compare models with and without safety cages, as well as models with optimal and constrained model parameters, and show that the weak supervision consistently improves the safety of exploration, speed of convergence, and model performance. Additionally, we show that when the model parameters are constrained or sub-optimal, the safety cages can enable a model to learn a safe driving policy even when the model could not be trained to drive through reinforcement learning alone.
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Wang, Qi, Ming Chai, Hongjie Liu y Tao Tang. "Optimized Control of Virtual Coupling at Junctions: A Cooperative Game-Based Approach". Actuators 10, n.º 9 (27 de agosto de 2021): 207. http://dx.doi.org/10.3390/act10090207.
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Recently, virtual coupling has aroused increasing interest in regard to achieving flexible and on-demand train operations. However, one of the main challenges in increasing the throughput of a train network is to couple trains quickly at junctions. Pre-programmed train operation strategies cause trains to decelerate or stop at junctions. Such strategies can reduce the coupling efficiency or even cause trains to fail to reach coupled status. To fill this critical gap, this paper proposes a cooperative game model to represent train coupling at junctions and adopts the Shapley theorem to solve the formulated game. Due to the discrete and high-dimensional characteristics of the model, the optimal solution method is non-convex and is difficult to solve in a reasonable amount of time. To find optimal operation strategies for large-scale models in a reasonable amount of time, we propose an improved particle swarm optimization algorithm by introducing self-adaptive parameters and a mutation method. This paper compares the strategy for train coupling at junctions generated by the proposed method with two naive strategies and unimproved particle swarm optimization. The results show that the operation time was reduced by using the proposed cooperative game-based optimization approach.
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Sands, Timothy. "Virtual Sensoring of Motion Using Pontryagin’s Treatment of Hamiltonian Systems". Sensors 21, n.º 13 (5 de julio de 2021): 4603. http://dx.doi.org/10.3390/s21134603.
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To aid the development of future unmanned naval vessels, this manuscript investigates algorithm options for combining physical (noisy) sensors and computational models to provide additional information about system states, inputs, and parameters emphasizing deterministic options rather than stochastic ones. The computational model is formulated using Pontryagin’s treatment of Hamiltonian systems resulting in optimal and near-optimal results dependent upon the algorithm option chosen. Feedback is proposed to re-initialize the initial values of a reformulated two-point boundary value problem rather than using state feedback to form errors that are corrected by tuned estimators. Four algorithm options are proposed with two optional branches, and all of these are compared to three manifestations of classical estimation methods including linear-quadratic optimal. Over ten-thousand simulations were run to evaluate each proposed method’s vulnerability to variations in plant parameters amidst typically noisy state and rate sensors. The proposed methods achieved 69–72% improved state estimation, 29–33% improved rate improvement, while simultaneously achieving mathematically minimal costs of utilization in guidance, navigation, and control decision criteria. The next stage of research is indicated throughout the manuscript: investigation of the proposed methods’ efficacy amidst unknown wave disturbances.
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Alexandru, Cătălin. "Modeling and Simulation in Virtual Prototyping Environment of a Photovoltaic Tracking System". Applied Mechanics and Materials 436 (octubre de 2013): 100–107. http://dx.doi.org/10.4028/www.scientific.net/amm.436.100.
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The paper presents the modeling and simulation of the mechatronic tracking system used for a photovoltaic module. The mechanical model of the sun tracker is developed by using the MBS environment ADAMS, while the DFC software EASY5 is used for the control system design. The study is approached in concurrent engineering concept, integrating the mechanical and control models at the virtual prototype level. The main task of the design refers to the energetic efficiency, by maximizing the energetic gain (i.e. the solar input), and minimizing the energy consumption for performing the tracking. The design of the motion law is focused on determining the optimal actuating times, considering the energetic efficiency as design objective for the optimization.
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Budia, I., A. Alvarez-Arenas, T. E. Woolley, G. F. Calvo y J. Belmonte-Beitia. "Radiation protraction schedules for low-grade gliomas: a comparison between different mathematical models". Journal of The Royal Society Interface 16, n.º 161 (diciembre de 2019): 20190665. http://dx.doi.org/10.1098/rsif.2019.0665.
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We optimize radiotherapy (RT) administration strategies for treating low-grade gliomas. Specifically, we consider different tumour growth laws, both with and without spatial effects. In each scenario, we find the optimal treatment in the sense of maximizing the overall survival time of a virtual low-grade glioma patient, whose tumour progresses according to the examined growth laws. We discover that an extreme protraction therapeutic strategy, which amounts to substantially extending the time interval between RT sessions, may lead to better tumour control. The clinical implications of our results are also presented.
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Sefercik, U. G., T. Kavzoglu, M. Nazar, C. Atalay y M. Madak. "UAV-BASED 3D VIRTUAL TOUR CREATION". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W5-2021 (23 de diciembre de 2021): 493–99. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w5-2021-493-2021.
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Abstract. Lately, improvements in game engines have increased the interest in virtual reality (VR) technologies, that engages users with an artificial environment, and have led to the adoption of VR systems to display geospatial data. Because of the ongoing COVID-19 pandemic, and thus the necessity to stay at home, VR tours became very popular. In this paper, we tried to create a three-dimensional (3D) virtual tour for Gebze Technical University (GTU) Southern Campus by transferring high-resolution unmanned air vehicle (UAV) data into a virtual domain. UAV data is preferred in various applications because of its high spatial resolution, low cost and fast processing time. In this application, the study area was captured from different modes and altitudes of UAV flights with a minimum ground sampling distance (GSD) of 2.18 cm using a 20 MP digital camera. The UAV data was processed in Structure from Motion (SfM) based photogrammetric evaluation software Agisoft Metashape and high-quality 3D textured mesh models were generated. Image orientation was completed using an optimal number of ground control points (GCPs), and the geometric accuracy was calculated as ±8 mm (~0.4 pixels). To create the VR tour, UAV-based mesh models were transferred into the Unity game engine and optimization processes were carried out by applying occlusion culling and space subdivision algorithms. To improve the visualization, 3D object models such as trees, lighting poles and arbours were positioned on VR. Finally, textual metadata about buildings and a player with a first-person camera were added for an informative VR experience.
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Podder, Amit Kumer, Sayemul Islam, Nallapaneni Manoj Kumar, Aneesh A. Chand, Pulivarthi Nageswara Rao, Kushal A. Prasad, T. Logeswaran y Kabir A. Mamun. "Systematic Categorization of Optimization Strategies for Virtual Power Plants". Energies 13, n.º 23 (27 de noviembre de 2020): 6251. http://dx.doi.org/10.3390/en13236251.
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Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.
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Lee, Sunmi, Okbun Baek y Luis Melara. "Resource Allocation in Two-Patch Epidemic Model with State-Dependent Dispersal Behaviors Using Optimal Control". Processes 8, n.º 9 (2 de septiembre de 2020): 1087. http://dx.doi.org/10.3390/pr8091087.
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A two-patch epidemic model is considered in order to assess the impact of virtual dispersal on disease transmission dynamics. The two-patch system models the movement of individuals between the two-patches using a residence-time matrix P, where P depends on both residence times and state variables (infected classes). In this work, we employ this approach to a general two-patch SIR model in order to investigate the effect of state dependent dispersal behaviors on the disease dynamics. Furthermore, optimal control theory is employed to identify and evaluate patch-specific control measures aimed at reducing disease prevalence at a minimal cost. Optimal policies are computed under various dispersal scenarios (depending on the different residence-time matrix configurations). Our results suggest there is a reduction of the outbreak and the proportion of time spent by individuals in a patch exhibits less fluctuations in the presence of patch-specific optimal controls. Furthermore, the optimal strategies for each patch differ depending on the type of dispersal behavior and the different infection rate in a patch. In all of our results, we obtain that the optimal strategies reduce the number of infections per patch.
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Horváth, László. "Supporting Lifecycle Management of Product Data by Organized Descriptions and Behavior Definitions of Engineering Objects". Journal of Advanced Computational Intelligence and Intelligent Informatics 11, n.º 9 (20 de noviembre de 2007): 1107–13. http://dx.doi.org/10.20965/jaciii.2007.p1107.
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Engineering for design, analysis, and manufacturing planning of products has been integrated with other product related engineering activities such as control of manufacturing equipment, marketing, sales and customer services in product lifecycle management systems (PLM). This challenging complex of activities would be impossible without the support of recent information technology (IT). Descriptions of various engineering objects have been integrated into very complex product models. Main area of development in the next future is enhanced assistance of decisions in product modeling. Approach to high level of modeling and application of the highly integrated product model for simulation will be the virtual intelligent space where all outside and inside effects are reacted. In order to join this tendency, this paper introduces a methodology for integrated application of analysis of behaviors of modeled objects, adaptive actions for controlled modifications of engineering objects, and definition of optimal sets of parameters. In order to establish a virtual intelligent space, sensor signals in physical intelligent space are replaced by received change information and actuators are replaced by adaptive actions. In this paper, new concept of intelligent virtual product space (IVPS) as integrated description of physical product and other objects and processes is introduced. Following this, a method is proposed to include computational intelligence in product models in the form of control of behaviors of modeled product objects. Change management methods are explained in close connection with behavior analysis. Finally, some methods for control of the work of a virtual intelligent product space are detailed.
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Alhuthali, Ahmed, Adedayo Oyerinde y Akhil Datta-Gupta. "Optimal Waterflood Management Using Rate Control". SPE Reservoir Evaluation & Engineering 10, n.º 05 (1 de octubre de 2007): 539–51. http://dx.doi.org/10.2118/102478-pa.
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Summary Field-scale rate optimization problems often involve highly complex reservoir models, production-and-facilities related constraints, and a large number of unknowns. These factors make optimal reservoir management through rate- and flood-front control difficult without efficient optimization tools. Some aspects of the optimization problem have been studied before mainly using an optimal control theory. However, the applications to date have been rather limited to small problems because of the computation time and the complexities associated with the formulation and solution of adjoint equations. Field-scale rate optimization for maximizing waterflood sweep efficiency under realistic field conditions has remained largely unexplored. This paper proposes a practical and efficient approach for computing optimal injection and production rates, thereby managing the waterflood front to maximize sweep efficiency and delaying the arrival time to minimize water cycling. Our work relies on equalizing the arrival times of the waterflood front at all producers within selected subregions of a waterflood project. The arrival-time optimization has favorable quasilinear properties, and the optimization proceeds smoothly even if our initial conditions are far from the solution. Furthermore, the sensitivity of the arrival time with respect to injection and production rates can be calculated analytically using a single-flow simulation. This makes our approach computationally efficient and suitable for large-scale field applications. The arrival time optimization ensures appropriate rate allocation and flood-front management by delaying the water breakthrough at the producing wells. Several examples are presented to support the robustness and efficiency of the proposed optimization scheme. These include several 2D-synthetic examples for validation purposes and a 3D field application. In addition, we demonstrate the potential of the approach to optimize the flow profile along injection/production segments of horizontal-smart wells. Introduction Waterflooding is by far the most commonly used method to improve oil recovery after primary depletion. In spite of its many favorable characteristics, reservoir heterogeneity—particularly permeability contrast—can have an adverse impact on the performance of waterflooding. The presence of high-permeability streaks can severely reduce the sweep efficiency, leading to an early water arrival at the producers and bypassed oil. Also, an increased cost is associated with water recycling and handling. One approach to counteract the impact of heterogeneity and improve waterflood sweep efficiency is optimal rate allocation to the injectors and producers (Asheim 1988; Sudaryanto and Yortsos 2001; Brouwer et al. 2001; Brouwer and Jansen 2004; Grinestaff 1999; Grinestaff and Caffrey 2000). Through optimal rate control, we can manage the propagation of the flood front, delay water breakthrough at the producers, and also increase the recovery efficiency. Previous efforts to optimize waterflooding relied on optimal control theorem to allocate injection/production rates for fixed well configurations. Asheim (1988) investigated the optimization of waterflood based on maximizing net present value (NPV) for multiple vertical injectors and one producer where the rate profiles change throughout the optimization time. Sudaryanto and Yortsos (2001) used maximizing the displacement efficiency at water breakthrough as the objective for the optimization with two injectors and one producer. The optimal injection policy was found to be bang bang type. That is, the injectors were operated only at their extreme values—either at the maximum allowable injection rate or fully shut. The optimization then involved finding the switch time between the two injectors to ensure simultaneous water arrival at the producing well. Brouwer et al. (2001) studied the static optimization of waterflooding with two horizontal smart wells containing permanent downhole well-control valves and measurement equipment. The static optimization implies that the flow rates of the inflow-control valves (ICVs) along the well segments were kept constant during the waterflooding process until the water arrived at the producer. Various heuristic algorithms were utilized to minimize the impact of high-permeability streaks on the waterflood performance through rate control. The results indicated that the optimal rate allocation can be obtained by reducing the distribution of water-arrival times at various segments along the producer. Subsequently, Brouwer and Jansen (2004) extended their work to dynamic optimization of waterflooding with smart wells using the optimal control theory. The optimization was performed on one horizontal producer and one horizontal injector. Each well is equipped with 45 ICVs. The objective was to maximize the NPV, and it was achieved through changing the rate profile along the well segments throughout the optimization period. Both rate-constrained and bottomhole-pressure-constrained well conditions were studied.
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Davuluri, P., S. Shetty, A. Dasgupta y S. Young. "Thermomechanical Durability of High I/O BGA Packages". Journal of Electronic Packaging 124, n.º 3 (26 de julio de 2002): 266–70. http://dx.doi.org/10.1115/1.1477192.
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Efficient modeling strategies are developed to study thermomechanical durability of high I/O Ball Grid Array (BGA) packages, in order to facilitate virtual qualification and accelerated testing of component designs. A viscoplastic stress analysis technique is developed where the critical solder joint(s) (joint(s) where failure first occurs) are modeled in detail with a multi-domain Rayleigh-Ritz (MDRR) methodology while the load-sharing offered by noncritical joints is modeled with a simplified compact model. This hybrid technique is used to study the behavior of solder interconnects in selected Ball Grid Array (BGA) package under thermal cycling environments. Parametric studies are conducted to determine the optimal scheme for allocating a critical number of solder joints to the MDRR model, and the remaining non-critical joints to the compact models. Damage calculations are made with the Energy Partitioning Solder Durability model and cycles-to-failure predictions are compared with both finite element model predictions as well as experimental failure data provided by CALCE EPSC sponsors. Parametric studies on change in solder joint durability with interconnect volume are also discussed in this paper.
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Zara, Jiri. "Web-Based Historical City Walks: Advances and Bottlenecks". Presence: Teleoperators and Virtual Environments 15, n.º 3 (1 de junio de 2006): 262–77. http://dx.doi.org/10.1162/pres.15.3.262.
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This paper deals with a set of useful methods for presenting large-scale models of real cities in a web environment. While acquisition issues are outlined only briefly, this study focuses on the optimal organization of city models and efficient rendering techniques. We also address data optimization for real-time delivery. The methods under discussion are illustrated by examples taken from several existing web presentations developed by our students, especially from the Virtual Old Prague project. Although the principles are general, specific attention is paid to the use of standards developed by the Web3D Consortium.
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Wang, Neng. "The Study on Partners Relationship for Virtual Enterprises Risk Management Based on Distributed Decision". Key Engineering Materials 439-440 (junio de 2010): 1024–29. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.1024.
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To reduce risks of Virtual Enterprise （VE）, a novel Distributed Decision Making （DDM） model for VE risk management was presented. This model had two levels, namely, the top-model and the base-model, which described the decision processes of the owner and the partners, respectively. The owner allocated funds to each member of the VE, the partners then selected their own optimal risk control actions to reduce their risks with the constraint given by the allocated budget. When number of members in VE, the number of risk factors and the number of actions increased, the size of the search space would be very huge, the brief solutions of the models are also discussed.
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Casius, L. J. Richard, Maarten F. Bobbert y Arthur J. van Soest. "Forward Dynamics of Two-Dimensional Skeletal Models. A Newton-Euler Approach". Journal of Applied Biomechanics 20, n.º 4 (noviembre de 2004): 421–49. http://dx.doi.org/10.1123/jab.20.4.421.
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Mathematical modeling and computer simulation play an increasingly important role in the search for answers to questions that cannot be addressed experimentally. One of the biggest challenges in forward simulation of the movements of the musculoskeletal system is finding an optimal control strategy. It is not uncommon for this type of optimization problem that the segment dynamics need to be calculated millions of times. In addition, these calculations typically consume a large part of the CPU time during forward movement simulations. As numerous human movements are two-dimensional (2-D) to a reasonable approximation, it is extremely convenient to have a dedicated, computational efficient method for 2-D movements. In this paper we shall present such a method. The main goal is to show that a systematic approach can be adopted which allows for both automatic formulation and solution of the equations of kinematics and dynamics, and to provide some fundamental insight in the mechanical theory behind forward dynamics problems in general. To illustrate matters, we provide for download an example implementation of the main segment dynamics algorithm, as well as a complete implementation of a model of human sprint cycling.
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Zharikov, E. V. y S. F. Telenyk. "Specialized software for simulating dynamic virtual machine consolidation". PROBLEMS IN PROGRAMMING, n.º 1 (marzo de 2022): 003–12. http://dx.doi.org/10.15407/pp2022.01.003.
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For many cloud service providers, virtual machines remain the basic technology for computing virtualization. Virtual machines are used both to host application software and to implement container virtualization. Widespread use of virtual machines develops specialized software to determine the impact of model parameters on the quality of the consolidation process, which will prevent experimental research in production to evaluate new cloud data center resource management strategies. In recent years, there were many approaches in literature that offers various sets of software tools and frameworks for modeling data center processes, providing a platform and the necessary building blocks to optimize the process of consolidation of virtual machines. Models and software tools for modeling data center resource management processes are usually not exhaustive and solve a specific problem or management task. The specialized simulation software presented in the paper allows to investigate different control modes of virtual machines dynamic consolidation, provides a wide range of logging and debugging information using text and MS Excel files, such as performance indicators and workload diagrams, and allows to determine the optimal model parameters for various modes of data center operation, minimizing the number of active physical servers and reducing the number of SLA violations.
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Baran, P., Y. Varetsky, V. Kidyba y Y. Pryshliak. "A mathematical model for the virtual simulator of the power unit electrical part". IOP Conference Series: Materials Science and Engineering 1216, n.º 1 (1 de enero de 2022): 012009. http://dx.doi.org/10.1088/1757-899x/1216/1/012009.
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Abstract The mathematical model is developed for a virtual training system (simulator) of the power unit electrical part operators of a thermal (nuclear) power plant. The model is used to simulating the main operating conditions of the power unit electrical part: generator idling, generator synchronization with the power system, excitation shifting from the main unit to the backup one and vice versa, switching in the power unit auxiliary system, and others. Furthermore, it has been implemented modelling some probable emergency conditions within a power plant: incomplete phase switching, damage to standard power unit equipment, synchronous oscillations, asynchronous mode, etc. The model of the power unit electrical part consists of two interacting software units: models of power equipment (turbine, generator with excitation systems, auxiliary system) and models of its control systems, automation, relay protection and signalling. The models are represented by the corresponding algebraic-differential equations that provide real-time mapping power unit processes at the operator’s request. The developed model uses optimal solving algebraic-differential equations to ensure the virtual process behaviour in real-time. In particular, the implicit Euler method is used to solve differential equations, which is stable when simulating processes in significant disturbances, such as accidental disconnection of the unit from the power system, tripping and energizing loads, generator excitation loss, etc.
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Ambrosini, Emilia, Monica Parati, Giorgio Ferriero, Alessandra Pedrocchi y Simona Ferrante. "Does cycling induced by functional electrical stimulation enhance motor recovery in the subacute phase after stroke? A systematic review and meta-analysis". Clinical Rehabilitation 34, n.º 11 (2 de julio de 2020): 1341–54. http://dx.doi.org/10.1177/0269215520938423.
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Objective: To investigate the effects of cycling with functional electrical stimulation on walking, muscle power and tone, balance and activities of daily living in subacute stroke survivors. Data Sources: Ten electronic databases were searched from inception to February 2020. Review methods: Inclusion criteria were: subacute stroke survivors (<6 months since stroke), an experimental group performing any type of cycling training with electrical stimulation, alone or in addition to usual care, and a control group performing usual care alone. Two reviewers assessed eligibility, extracted data and analyzed the risks of bias. Standardized Mean Difference (SMD) or Mean Difference (MD) with 95% Confidence Intervals (CI) were estimated using fixed- or random-effects models to evaluate the training effect. Results: Seven randomized controlled trials recruiting a total of 273 stroke survivors were included in the meta-analyses. There was a statistically significant, but not clinically relevant, effect of cycling with electrical stimulation compared to usual care on walking (six studies, SMD [95% CI] = 0.40 [0.13, 0.67]; P = 0.004), capability to maintain a sitting position (three studies, MD [95% CI] = 7.92 [1.01, 14.82]; P = 0.02) and work produced by the paretic leg during pedaling (2 studies, MD [95% CI] = 8.13 [1.03, 15.25]; P = 0.02). No significant between-group differences were found for muscular power, tone, standing balance, and activities of daily living. Conclusions: Cycling training with functional electrical stimulation cannot be recommended in terms of being better than usual care in subacute stroke survivors. Further investigations are required to confirm these results, to determine the optimal training parameters and to evaluate long-term effects.
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Anderson, P. S. L. y E. J. Rayfield. "Virtual experiments, physical validation: dental morphology at the intersection of experiment and theory". Journal of The Royal Society Interface 9, n.º 73 (7 de marzo de 2012): 1846–55. http://dx.doi.org/10.1098/rsif.2012.0043.
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Computational models such as finite-element analysis offer biologists a means of exploring the structural mechanics of biological systems that cannot be directly observed. Validated against experimental data, a model can be manipulated to perform virtual experiments, testing variables that are hard to control in physical experiments. The relationship between tooth form and the ability to break down prey is key to understanding the evolution of dentition. Recent experimental work has quantified how tooth shape promotes fracture in biological materials. We present a validated finite-element model derived from physical compression experiments. The model shows close agreement with strain patterns observed in photoelastic test materials and reaction forces measured during these experiments. We use the model to measure strain energy within the test material when different tooth shapes are used. Results show that notched blades deform materials for less strain energy cost than straight blades, giving insights into the energetic relationship between tooth form and prey materials. We identify a hypothetical ‘optimal’ blade angle that minimizes strain energy costs and test alternative prey materials via virtual experiments. Using experimental data and computational models offers an integrative approach to understand the mechanics of tooth morphology.
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Gu, Xueqiang, Lincheng Shen, Jing Chen, Yu Zhang y Wanpeng Zhang. "A Virtual Motion Camouflage Approach for Cooperative Trajectory Planning of Multiple UCAVs". Mathematical Problems in Engineering 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/748974.
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This paper investigates cooperative trajectory planning of multiple unmanned combat aerial vehicles (multi-UCAV) in performing autonomous cooperative air-to-ground target attack missions. By integrating an approximate allowable attack region model, several constraint models, and a multicriterion objective function, the problem is formulated as a cooperative trajectory optimal control problem (CTOCP). Then, a virtual motion camouflage (VMC) for cooperative trajectory planning of multi-UCAV, combining with the differential flatness theory, Gauss pseudospectral method (GPM), and nonlinear programming, is designed to solve the CTOCP. In particular, the notion of the virtual time is introduced to the VMC problem formulation to handle the temporal cooperative constraints. The simulation experiments validate that the CTOCP can be effectively solved by the cooperative trajectory planning algorithm based on VMC which integrates the spatial and temporal constraints on the trajectory level, and the comparative experiments illustrate that VMC based algorithm is more efficient than GPM based direct collocation method in tackling the CTOCP.
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Enescu, Monica y Cătălin Alexandru. "Optimal Design of the Control System for an Industrial Robot Using DOE Technique and Regression Model". Applied Mechanics and Materials 658 (octubre de 2014): 626–31. http://dx.doi.org/10.4028/www.scientific.net/amm.658.626.
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This paper approaches the optimization of the control system for an industrial robot with 6 axes (degrees of freedom), using design of experiments (DOE) and multiple linear regression models. The design objective refers to the desired trajectory of the end-effector, the aim being to minimize the difference between the desired (imposed) and current (measured) angles in the revolute joints of the robot. The correlation between the imposed trajectory of the end-effector and the corresponding angular motions in the six revolute joints is obtained through the inverse kinematic analysis. The characteristic parameters of the controllers are used as design variables in the optimization. The optimal design is based on the DOE Screening investigation strategy with the Full Factorial design type. This design was chosen in order to evaluate the effect of the factors and of their interaction on trajectory, and the levels of these factors needed to produce an optimal trajectory. By comparing actual data with data after optimization, it shows that the regression function is correct (in terms of goodness of fit). The dynamic model of the robotic system was developed in mechatronic concept, by integrating the mechanical device (designed in ADAMS/View) and the control system (MATLAB/Simulink) at the virtual prototype level. The optimization study is performed by using ADAMS/Insight.
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Smoker, Jason, Amr Baz y Ling Zheng. "Virtual Reality Simulation of Active Car Suspension System". International Journal of Virtual Reality 8, n.º 2 (1 de enero de 2009): 75–82. http://dx.doi.org/10.20870/ijvr.2009.8.2.2728.
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This paper presents the design of a Nonlinear Energy Sink (NES) controller and its application to active sus-pension systems in the Virtual Reality Environment. In this en-vironment, the design engineers are immersed in an audio-visually coupled tele-operated environment whereby direct in-teraction with and control of the design process is achieved in real time. In this manner, the behavior of synthetic models of the full car can be monitored by literally walking around the car and adjusting the design parameters of the suspension as needed to ensure optimal performance while satisfying design and operational requirements. The control actuators which provide forces equivalent to nonlinear stiffness and damping elements are attached to the vehicle in order to actively isolate it from road excitation. The effect of the parameters of the NES controller on the vehicle performance is studied both in the frequency and time domain. The effectiveness of the NES controller is validated by numeri-cal simulation. The robustness of the nonlinear energy pumping process is studied by varying the magnitude of road excitation. The simulation results in the Virtual Reality Environment show that under certain conditions, the nonlinear energy pumping can be induced and significant vibration isolation can be achieved. The performance of vehicle including the ride com-fort and road holding capability can be improved significantly. When the magnitude of road excitation is increased, the capaci-ty of the NES to absorb energy from the main system is also enhanced. This is very important to achieve vibration isolation objectives. The virtual reality simulation results also show that the nonlinear NES controller performs better than the classical LQR controller particularly as the road condition becomes worst.
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Diachuk, Maksym y Said M. Easa. "Modeling Combined Operation of Engine and Torque Converter for Improved Vehicle Powertrain’s Complex Control". Vehicles 4, n.º 2 (23 de mayo de 2022): 501–28. http://dx.doi.org/10.3390/vehicles4020030.
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This paper proposes an alternative model for describing the hydro-mechanical drive operation of the automatic transmissions. The study is aimed at preparing a reliable model that meets the requirements of sufficient informativeness and rapidity to, basically, be used as a model for optimized control. The study relevance is stipulated by the need for simple and precise models ensuring minimal computational costs in model predictive control (MPC) procedures. The paper proposes a method for coordinating the engine’s control and operating modes, with the torque converter (TC) operating mode, based on the criteria of angular acceleration derivative (jerk), which fosters including the angular acceleration in the state vector for using the optimal control. The latter provides stronger prediction quality than using only the crankshaft angular speed criterion. This moment comprises a study novelty. Additionally, the proposed approach can be helpful in tasks of powertrain automation, autonomous vehicles’ integrated control, elaboration of control algorithms, co-simulations, and real-time applications. The paper material is structured by the modeling stages, including mathematics and simulations, data preparation, testing and validation, virtual experiments, analysis of results, and conclusions. The essence of the problem, goals, and objectives are first presented, followed by the overview of main approaches in modeling the automatic transmission elements. The internal combustion engine (ICE), torque converter, drivetrain, tires, and translational dynamics mathematical models are determined and discussed in detail. The proposed approach convergence on decomposing the indicators of powertrain aggregates by derivatives is demonstrated. The considered method was simulated by using the data of the Audi A4 Quattro. The gear shifting control algorithm was described in detail, and a series of virtual tests for the composed model were carried out. The comparative analysis of the results for the conventional and advanced models of the automatic transmission’s hydro-mechanical drive were performed. The differences of the model outputs were discussed. The approach advantages were noted, as well as the options for extending the proposed technique.
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Sierra, Daniel A. y John D. Enderle. "3D Dynamic Modeling of the Head-Neck Complex for Fast Eye and Head Orientation Movements Research". Modelling and Simulation in Engineering 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/630506.
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A 3D dynamic computer model for the movement of the head-neck complex is presented. It incorporates anatomically correct information about the diverse elements forming the system. The skeleton is considered as a set of interconnected rigid 3D bodies following the Newton-Euler laws of movement. The muscles are modeled using Enderle's linear model, which shows equivalent dynamic characteristics to Loeb's virtual muscle model. The soft tissues, namely, the ligaments, intervertebral disks, and facet joints, are modeled considering their physiological roles and dynamics. In contrast with other head and neck models developed for safety research, the model is aimed to study the neural control of the complex during fast eye and head movements, such as saccades and gaze shifts. In particular, the time-optimal hypothesis and the feedback control ones are discussed.
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Sniders, Andris y Toms Komass. "Invariant Method of Load Independent Pressure Control in Steam Boiler". Electrical, Control and Communication Engineering 1, n.º 1 (1 de diciembre de 2012): 5–10. http://dx.doi.org/10.2478/v10314-012-0001-4.
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Abstract The paper considers the possibility of steam production and supply process improvement by perfection of the steam boiler control system, applying invariance principle that makes possible preemptive compensation of the influence of steam expenditure as a disturbance on the control process quality and efficiency. For the development of invariant control system, the mathematical modeling and simulation in MATLAB - SIMULINK environment is made. The control unit is low pressure steam boiler with one input impact to control - the heat flow of burning gas mixture fuel, one measured output parameter of the process - the steam pressure, and the main disturbance as a load impact - the steam expenditure. The mathematical and virtual models and block-diagrams for transient process simulation is compiled, allowing to start practical design and investigation of steam boiler invariant control system with high operation stability under essentially fluctuating load. The simulation results prove that the optimal solution for the transient process improvement in steam boiler, taking in account fluctuating load, is invariant PID-DPC two loop control system with disturbance impact on steam pressure preemptive compensation. Under invariant control the steam pressure overshoots decreases substantially in comparison with the traditional PID-feedback control method.
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Saushev, Alexandr, Vladimir Tyrva y Lev Kovtun. "Joint control actions on electromechanical devices in ergatic systems". E3S Web of Conferences 135 (2019): 01006. http://dx.doi.org/10.1051/e3sconf/201913501006.
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The problem of implementing joint control actions on electromechanical devices (EMD) in human-machine systems through the control body of a human-machine interface is considered. Based on the theory of optimal control, control functions between the human operator, the program control automaton, and the corrective control automaton are synthesized. Peculiarities of the technical implementation of the control actions on the EMD of the ergatic system using the new type of joint control devices have been identified, through the control body of which information interaction between the human operator and the system automa-ton is carried out. Based on the model of actions and responses of the human operator and machine, which is adopted in engineering psychology, mathematical models of their joint control of the object have been developed. Mathematical models of machine responses are constructed using the hypothesis of complete certainty in the form of a normal system of ordinary differen-tial equations. As a result of combining action and response models for the human-machine system, a finite set of incomplete representations of the elementary motions of the image point in the state space is obtained, on which the programmed motion of the object is built in the form of a sequence of elementary motions. Virtual discrete control signals Corresponding to specific positions of the control bodies of the joint control apparatuses of the human-machine interface of the system are determined, through which consecutive transitions from one elementary movement to another are carried out. The conclusions on the effectiveness of the use of joint control in transport ergatic human-machine systems are formulated. It is shown that in this case, the advantages of control partners are used and combined to the greatest extent.
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Pan, Chenyun, Shengyu Tao, Hongtao Fan, Mengyao Shu, Yong Zhang y Yaojie Sun. "Multi-Objective Optimization of a Battery-Supercapacitor Hybrid Energy Storage System Based on the Concept of Cyber-Physical System". Electronics 10, n.º 15 (28 de julio de 2021): 1801. http://dx.doi.org/10.3390/electronics10151801.
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Optimal operation of energy storage systems plays an important role in enhancing their lifetime and efficiency. This paper combines the concepts of the cyber–physical system (CPS) and multi-objective optimization into the control structure of the hybrid energy storage system (HESS). Owing to the time-varying characteristics of HESS, combining real-time data with physical models via CPS can significantly promote the performance of HESS. The multi-objective optimization model designed in this paper can improve the utilization of supercapacitors, reduce energy consumption, and prevent the state of charge (SOC) of HESS from exceeding the limitation. The new control scheme takes the characteristics of the components of HESS into account and is beneficial in reducing battery short-term power cycling and high discharge currents. The rain-flow counting algorithm is applied for battery life prediction to quantify the benefits of the HESS under the control scheme proposed. A much better power-sharing relationship between the supercapacitor and the lithium–ion battery (LiB) can be observed from the SIMULINK results and the case study with our new control scheme. Moreover, compared to the traditional low-pass filter control method, the battery lifetime is quantifiably increased from 3.51 years to 10.20 years while the energy efficiency is improved by 1.56%.
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Wang, Zhujun, Xuyuan Tao, Xianyi Zeng, Yingmei Xing, Yanni Xu, Zhenzhen Xu, Pascal Bruniaux y Jianping Wang. "An Interactive Personalized Garment Design Recommendation System Using Intelligent Techniques". Applied Sciences 12, n.º 9 (6 de mayo de 2022): 4654. http://dx.doi.org/10.3390/app12094654.
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This paper presents a garment design recommendation system based on two mathematical models that permit the prediction and control of garment styles and structural parameters from a consumer’s personalized requirements in terms of fitting and aesthetics. Based on a formalized professional garment knowledge base, enabling the quantitative characterization of the relations between consumer profiles and garment profiles (colors, fabrics, styles, and garment fit), these two models aim at recommending the most relevant garment profile from a specific consumer profile, using reasoning with fuzzy rules and self-adjusting the garment patterns according to the feedback of the 3D virtual fitting effects corresponding to the recommended garment profile, using a genetic algorithm (GA) and support vector regression. Based on these knowledge-based models, the proposed interactive recommendation system enables the progressive optimization of the design solution through a series of human–machine interactions, i.e., the repeated execution of the cycle “design generation—virtual garment demonstration—user’s evaluation—adjustment” until the satisfaction of the end user (consumer or designer). The effectiveness of this interactive recommendation system was validated by a real case of pants customization. In a manner different from the existing approaches, the proposed system will enable designers to rapidly, accurately, intelligently, and automatically generate the optimal design solution, which is relevant in dealing with mass customization and e-shopping for fashion companies.
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Wooliscroft, Lindsey, Sharon McCoy, Andrea Hildebrand, William Rooney, Barry S. Oken, Rebecca Irene Spain, Kerry S. Kuehl, Dennis Bourdette y Michelle Cameron. "Protocol for an exploratory, randomised, single-blind clinical trial of aerobic exercise to promote remyelination in multiple sclerosis". BMJ Open 13, n.º 1 (enero de 2023): e061539. http://dx.doi.org/10.1136/bmjopen-2022-061539.
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IntroductionThere is an urgent need for remyelinating therapies that restore function in people with multiple sclerosis (pwMS). Aerobic exercise is a promising remyelinating strategy because it promotes remyelination in animal models both independently and synergistically with medications. Here, in this study, we present an innovative, randomised, single-blind, clinical trial designed to explore: the relationship between demyelination and mobility (part 1), and if 24 weeks of aerobic exercise promotes remyelination in pwMS (part 2).Methods and analysisSedentary participants (n=60; aged 18–64 years) with stable MS will undergo a baseline visit with the following outcomes to assess associations between demyelination and mobility (part 1): spinal cord demyelination (somatosensory-evoked potentials, SSEPs), mobility (6-Minute Timed Walk, Timed 25-Foot Walk, Timed Up and Go, 9-Hole Peg Test) and patient-reported outcomes (PROs). After baseline testing, participants with significantly prolonged SSEP latency will advance to the clinical exercise trial (part 2) and will be randomised 1:1 to active or control conditions for 24 weeks. The active condition will be aerobic stationary cycling three times per week with graded virtual supervision. The control condition will be monthly virtual MS symptom education groups (six sessions). SSEP latency (remyelination endpoint), mobility outcomes and PROs will be measured at 12 and 24 weeks in all clinical trial participants. A subset of 11 active and 11 control participants will undergo a brain MRI with quantitative T1myelin water fraction at baseline and 24 weeks (exploratory remyelination endpoint).Ethics and disseminationEthical approval was obtained from the Oregon Health & Science University Institutional Review Board (#21045). Dissemination of findings will include peer-reviewed publications, conference presentations and media releases. The proposed study will inform the feasibility, study design and sample size for a fully powered clinical trial of aerobic exercise to promote remyelination in pwMS.Trial registration numberNCT04539002.
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Zhai, Shike, Yixin Shi, Junchi Zhou, Jianfei Liu, Defan Huang, Airu Zou y Ping Jiang. "Simulation Optimization and Experimental Study of the Working Performance of a Vertical Rotary Tiller Based on the Discrete Element Method". Actuators 11, n.º 12 (23 de noviembre de 2022): 342. http://dx.doi.org/10.3390/act11120342.
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In order to investigate the mechanism of interaction between a vertical rotary tiller and the soil to obtain the best structural and operational parameters of the tool, improve the operational quality of the rotary tiller, achieve the effect of soil breaking and leveling to meet the agronomic requirements of tillage, a series of simulation tests was conducted through the design of 3D models of rotary tillers with different structural forms and the building of discrete element models of the action between the rotary tiller and the soil. The virtual simulation of different operating parameters and structural parameters of vertical rotary tiller was carried out by EDEM, and the effects of operating parameters, tool bending angle, and cutter installation number on the operating effect were analyzed. The parameter combination with the best operating effect was obtained through orthogonal test analysis and verified by soil trough test. A soil tank test showed that, with the optimal combination of operating and structural parameters, the average soil breaking rate of the vertical rotary tiller was 81.3%, which meets the agronomic requirements of tillage operation, and the actual power consumption was 6% higher than the simulation value, which was sufficiently close to verify the validity of the simulation. This study can lay a foundation for optimization research on the vertical miniature rotary tiller.
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Wang, Ziwen, Baichun Gong, Yanhua Yuan y Xin Ding. "Incomplete Information Pursuit-Evasion Game Control for a Space Non-Cooperative Target". Aerospace 8, n.º 8 (3 de agosto de 2021): 211. http://dx.doi.org/10.3390/aerospace8080211.
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Aiming to solve the optimal control problem for the pursuit-evasion game with a space non-cooperative target under the condition of incomplete information, a new method degenerating the game into a strong tracking problem is proposed, where the unknown target maneuver is processed as colored noise. First, the relative motion is modeled in the rotating local vertical local horizontal (LVLH) frame originated at a virtual Chief based on the Hill-Clohessy-Wiltshire relative dynamics, while the measurement models for three different sensor schemes (i.e., single LOS (line-of-sight) sensor, LOS range sensor and double LOS sensor) are established and an extended Kalman Filter (EKF) is used to obtain the relative state of target. Next, under the assumption that the unknown maneuver of the target is colored noise, the game control law of chaser is derived based on the linear quadratic differential game theory. Furthermore, the optimal control law considering the thrust limitation is obtained. After that, the observability of the relative orbit state is analyzed, where the relative orbit is weakly observable in a short period of time in the case of only LOS angle measurements, fully observable in the cases of LOS range and double LOS measurement schemes. Finally, numerical simulations are conducted to verify the proposed method. The results show that by using the single LOS scheme, the chaser would firstly approach the target but then would lose the game because of the existence of the target’s unknown maneuver. Conversely, the chaser can successfully win the game in the cases of LOS range and double LOS sensor schemes.
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Xie, Yuanlong, Xiaoqi Tang, Bao Song, Xiangdong Zhou y Yixuan Guo. "Model-free tuning strategy of fractional-order PI controller for speed regulation of permanent magnet synchronous motor". Transactions of the Institute of Measurement and Control 41, n.º 1 (5 de febrero de 2018): 23–35. http://dx.doi.org/10.1177/0142331217751040.
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This paper investigates a model-free tuning method of a fractional-order proportional–integral (FOPI) controller and its application for the speed regulation of a permanent magnet synchronous motor (PMSM). Firstly, the presented practical FOPI tuning method formulates the FOPI controller parameter identification problem via virtual reference feedback tuning (VRFT). Under the lack of accurate models, the proposed model-free method depends only on the measured input–output data of the closed-loop PMSM servo system. Secondly, Bode’s ideal transfer function is incorporated into the VRFT with consideration of the systematic fractional dynamics. Thus, the properties of the resulting system may be approximated to the desired fractional-order reference model. Thirdly, the proposed method fully considers optimal performance constraints on the stability requirements, sensitivity criteria, frequency-domain and time-domain characteristics. Then, the comprehensive optimization problem is derived and solved. Using suitably tuned parameters, the robustness and disturbance rejection ability of the VRFT-based FOPI control system are enhanced to achieve optimal performance. The convergence of the proposed method is proved by theoretical analysis. Finally, experimental results are presented to illustrate the effectiveness of the proposed model-free FOPI control method for the PMSM servo system.
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Romanov, O. I., I. V. Svyd, N. I. Korniienko y A. O. Romanov. "Optical Network Management by ONOS-Based SDN Controller". Radiotekhnika, n.º 210 (28 de septiembre de 2022): 188–96. http://dx.doi.org/10.30837/rt.2022.3.210.16.
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The possibilities to manage the optical network with a logically centralized SDN control plane based on the Open Network Operating System (ONOS) are investigated. The structure of the controller and its main functional blocks are considered ensuring the collection of information about the state of network elements, the solution of the main control tasks, interaction of control systems built on different technological bases, are considered. The role and place of the open network operating system in the controller structure are shown, the description of the ONOS multilevel architecture in the form of a set of functional modules is given, the purpose and functions of the ONOS subsystems are analyzed, protocols and interfaces making it possible to present the SDN network as a model are described. The peculiarity of the model is that the managed network can be represented as a set of virtual network functions. Therefore, the control process becomes independent of which vendor's equipment was used to build the network, as well as whether the network is built on real physical elements or virtual ones. Using the ONOS allows you to build a logical centralized control plane in the SDN networks. The existing set of functional modules, services and interfaces in the ONOS allows you to perform optical network management tasks. For the further development of the ONOS, it is necessary to develop mathematical models and methods for the optimal solution of control problems in various operating conditions, which will become application-level software modules in the future.
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Ke, Fang, Zachary Benet y Irina L. Grigorova. "Dual role of CCL3 and follicular regulatory T cells in the control of germinal center response". Journal of Immunology 206, n.º 1_Supplement (1 de mayo de 2021): 24.09. http://dx.doi.org/10.4049/jimmunol.206.supp.24.09.
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Abstract Follicular regulatory T cells (Tfrs) have been reported to play multiple roles in the control of B cells response. They repress foreign antigen-specific germinal center (GC) B cells at the peak of GC response. At the same time, under some conditions they promote GC B cell cycling in IL-10 dependent fashion and ensure optimal affinity maturation. Our previous studies suggested that CCL3 produced by GC centrocytes (CCs) promoted their direct contacts with Tfr cells and negative regulation of GC B cells at the peak of GC response. However, which fraction of CCs upregulates CCL3 expression, which receptors on Tfrs may respond to CCL3, and the long-term effect of CCL3 on GCs has been unclear. Based on the single cell and bulk qPCR analysis we found that CCL3 is upregulated in about 10% of CCs that express Myc and are undergoing positive selection. qPCR and transwell analysis revealed expression and synergistic involvement of CCR5 and CCR1 chemokine receptors on Tfr cells in their chemotaxis to CCL3. Interestingly, both an adoptive transfer and mixed bone marrow chimeras models suggest that after the peak of GC response B cell-intrinsic production of CCL3 promotes their prolonged participation in GCs and B cell affinity maturation, as well as better memory and plasmablast response. We also showed that both the negative and positive regulation of GC B cells by CCL3 was dependent on the presence of Tregs. To summarize, our studies suggest that in addition to the role of CCL3 and Tregs in the modest repression of foreign antigen-specific B cells at the peak of GC response, it is also important for optimal selection of B cells in GCs. Further studies are underway to determine the role of Tfr cells specifically in the negative and positive CCL3-mediated regulation of GCs.
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Ouadoudi, Marouane, Michael H. Schwarz y Josef Borcsok. "Development of a Digital Twin for an Elevator System". WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 17 (4 de mayo de 2022): 214–21. http://dx.doi.org/10.37394/23203.2022.17.25.
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The increasing digitalization of production processes and current technological developments make it possible to use sophisticated digital product models or virtual images of industrial and technical processes, so called digital twins. In this paper a digital twin is created using different development environments and systems, such as Simulink®, B&R® control, CAD design environment and OPC-UA communication. The creation process used is verified and simulations are performed with the created digital twin to test and validate its behavior and efficiency compared with the physical model. Then the two systems, which are the digital twin and the elevator model, are linked together so that the communication between the two can be verified. The ability to communicate with the real world is one of the main characteristics of an optimal digital twin.
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Mahapatra, Abhijit, Shibendu Shekhar Roy y Dilip Kumar Pratihar. "Optimal Feet-Forces’ and Torque Distributions of Six-Legged Robot Maneuvering on Various Terrains". Robotica 38, n.º 6 (15 de agosto de 2019): 1041–63. http://dx.doi.org/10.1017/s0263574719001243.
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SUMMARYAn analytical model with coupled dynamics for a realistic six-legged robotic system locomoting on various terrains has been developed, and its effectiveness has been proven through computer simulations and validated using virtual prototyping tools and real experiment. The approach is new and has not been attempted before. This study investigated the optimal feet-forces’ distributions under body force and foot–ground interaction considering compliant contact and friction force models for the feet undergoing slip. The kinematic model with 114 implicit constraints in 3D Cartesian space has been transformed in terms of generalized coordinates with a reduced explicit set of 24 constrained equations using kinematic transformations. The nonlinear constrained inverse dynamics model of the system has been formulated as a coupled dynamical problem using Newton–Euler method with realistic environmental conditions (compliant foot–ground contact, impact, and friction) and computed using optimization techniques due to its indeterminate nature. One case study has been carried out to validate the analytical data with the simulated ones executed in MSC.ADAMS® (Automated Dynamic Analysis of Mechanical Systems), while the other case study has been conducted to validate the analytical and simulated data with the experimental ones. In both these cases, results are found to be in close agreement, which proves the efficacy of the model.
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G. M. Abdolrasol, Maher, Mahammad Abdul Hannan, S. M. Suhail Hussain, Taha Selim Ustun, Mahidur R. Sarker y Pin Jern Ker. "Energy Management Scheduling for Microgrids in the Virtual Power Plant System Using Artificial Neural Networks". Energies 14, n.º 20 (11 de octubre de 2021): 6507. http://dx.doi.org/10.3390/en14206507.
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This study uses an artificial neural network (ANN) as an intelligent controller for the management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP). Two ANN-based scheduling control approaches are presented: the ANN-based backtracking search algorithm (ANN-BBSA) and ANN-based binary practical swarm optimization (ANN-BPSO) algorithm. Both algorithms provide the optimal schedule for every distribution generation (DG) to limit fuel consumption, reduce CO2 emission, and increase the system efficiency towards smart and economic VPP operation as well as grid decarbonization. Different test scenarios are executed to evaluate the controllers’ robustness and performance under changing system conditions. The test cases are different load curves to evaluate the ANN’s performance on untrained data. The untrained and trained load models used are real-load parameter data recorders in northern parts of Malaysia. The test results are analyzed to investigate the performance of these controllers under varying power system conditions. Additionally, a comparative study is performed to compare their performances with other solutions available in the literature based on several parameters. Results show the superiority of the ANN-based controllers in terms of cost reduction and efficiency.
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Kovaliuk, Dmytro, Ruslan Osipa y Victoria Кondratova. "Decision making in control systems based on data analysis". Proceedings of the NTUU “Igor Sikorsky KPI”. Series: Chemical engineering, ecology and resource saving, n.º 4 (24 de diciembre de 2021): 30–38. http://dx.doi.org/10.20535/2617-9741.4.2021.248902.
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Technological processes are always accompanied by deviations from the set mode, which is due to the influence of many external and internal factors. The environmental parameters, the components of input raw materials, and the condition of technological equipment are constantly changing, which requires solving the problem of finding the optimal control parameters and, in some cases, the parameters of the process itself.
Most industries are focused on obtaining the final product with a given level of quality. Changes in parameters of the technological process may deteriorate the quality of production and cause defects or even emergency situations. To prevent this, forecasting methods are used.
The task of constructing predictive models based on experimental data is relevant for a wide range of technological processes. Today, predictive models are widely used in management, diagnosis and identification. The vast majority of these models are based on artificial intelligence technologies or methods of mathematical statistics.
The most widespread forecasting models find application in areas such as banking, insurance, business economics, medicine, diagnostics of technical components and equipment, and forecasting the parameters of technological processes.
Despite the well-developed algorithm for model development and application, the main problem that remains is to acquire data, select an appropriate model structure, and integrate the model into existing control systems.
The paper will predict the parameters of the technological process of methanol production under reduced pressure. The production of methanol under reduced pressure is a multi-stage process, and the emergence of problems at some stage will adversely affect further work and the end result.
Note that there are all problems related to the performance of technological processes in the production of methanol, which are described above. Therefore, another task is to forecast emergencies, taking into account the indicators of all stages in the process. The development of models for forecasting emergencies and controlling thermal regimes and their further integration into the existing automatic process control system is proposed to be performed according to the principles of industrial revolution – Industry 4.0.
Important components of Industry 4.0 are the Internet of Things, data analysis, and digital duplicates. Each of these components solves a partial problem and, collectively, they provide full automation of production, forecasting of real-time process indicators, and calculation of optimal control.
The process of methanol production under reduced pressure can be fully automated in accordance with the components of Industry 4.0. First, there is instrumentation that allows the values of technological process to be obtained over time. Second, given a moderate size of these data, one can obtain models of control objects, perform their software implementation, and use them to calculate optimal control or predict the state of the process.
The paper proposes a variant of constructing a virtual model based on experimental data and its further use with actual values of process parameters.
A regression model was chosen to develop a model for predicting the temperature regime. Regression analysis allows checking the statistical significance of the parameters, assessing the adequacy and accuracy of the model, and establishing the nature and closeness of the relationship between the studied phenomena.
It is also important to predict the occurrence of emergency (adverse) situations at the workplace. For this purpose, it is necessary to determine a list of these situations according to the technological regulations and develop a model for forecasting emergencies. There are various forms of presenting a model for forecasting emergencies. A decision tree is one of them. It will be developed for the production of methanol.
The resulting tree is a graphical structure of the verbal (semantic) model relying on the expert's reasoning in solving problems related to emergencies. This is a network structure, whose nodes indicate potential deviations of the control object from the normal mode of operation. The resulting tree is used to solve forecasting and diagnosing problems.
For practical use, the decision tree is implemented in software as an "if - then" set of rules. The software is used as an element of a higher-level system in relation to the existing automatic process control system.
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Nica, Diana Florina, Alin Gabriel Gabor, Virgil-Florin Duma, Vlad George Tudericiu, Anca Tudor y Cosmin Sinescu. "Sinus Lift and Implant Insertion on 3D-Printed Polymeric Maxillary Models: Ex Vivo Training for In Vivo Surgical Procedures". Journal of Clinical Medicine 10, n.º 20 (14 de octubre de 2021): 4718. http://dx.doi.org/10.3390/jcm10204718.
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Background and Objectives: The aim of this study is to demonstrate the increased efficiency achieved by dental practitioners when carrying out an ex vivo training process on 3D-printed maxillaries before performing in vivo surgery. Materials and Methods: This developed ex vivo procedure comprises the following phases: (i) scanning the area of interest for surgery; (ii) obtaining a 3D virtual model of this area using Cone Beam Computed Tomography (CBCT); (iii) obtaining a 3D-printed model (based on the virtual one), on which (iv) the dental practitioner simulates/rehearses ex vivo (most of) the surgery protocol; (v) assess with a new CBCT the 3D model after simulation. The technical steps of sinus augmentation and implant insertion could be performed on the corresponding 3D-printed hemi-maxillaries prior to the real in vivo surgery. Two study groups were considered, with forty patients divided as follows: Group 1 comprises twenty patients on which the developed simulation and rehearsal procedure was applied; Group 2 is a control one which comprises twenty patients on which similar surgery was performed without this procedure (considered in order to compare operative times without and with rehearsals). Results: Following the ex vivo training/rehearsal, an optimal surgery protocol was developed for each considered case. The results of the surgery on patients were compared with the results obtained after rehearsals on 3D-printed models. The performed quantitative assessment proved that, using the proposed training procedure, the results of the in vivo surgery are not significantly different (p = 0.089) with regard to the ex vivo simulation for both the mezio-distal position of the implant and the distance from the ridge margin to sinus window. On the contrary, the operative time of Group 1 was reduced significantly (p = 0.001), with an average of 20% with regard to in vivo procedures performed without rehearsals (on the control Group 2). Conclusions: The study demonstrated that the use of 3D-printed models can be beneficial to dental surgeon practitioners, as well as to students who must be trained before performing clinical treatments.
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Lim, Seung-Ho, WoonSik William Suh, Jin-Young Kim y Sang-Young Cho. "RISC-V Virtual Platform-Based Convolutional Neural Network Accelerator Implemented in SystemC". Electronics 10, n.º 13 (23 de junio de 2021): 1514. http://dx.doi.org/10.3390/electronics10131514.
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The optimization for hardware processor and system for performing deep learning operations such as Convolutional Neural Networks (CNN) in resource limited embedded devices are recent active research area. In order to perform an optimized deep neural network model using the limited computational unit and memory of an embedded device, it is necessary to quickly apply various configurations of hardware modules to various deep neural network models and find the optimal combination. The Electronic System Level (ESL) Simulator based on SystemC is very useful for rapid hardware modeling and verification. In this paper, we designed and implemented a Deep Learning Accelerator (DLA) that performs Deep Neural Network (DNN) operation based on the RISC-V Virtual Platform implemented in SystemC in order to enable rapid and diverse analysis of deep learning operations in an embedded device based on the RISC-V processor, which is a recently emerging embedded processor. The developed RISC-V based DLA prototype can analyze the hardware requirements according to the CNN data set through the configuration of the CNN DLA architecture, and it is possible to run RISC-V compiled software on the platform, can perform a real neural network model like Darknet. We performed the Darknet CNN model on the developed DLA prototype, and confirmed that computational overhead and inference errors can be analyzed with the DLA prototype developed by analyzing the DLA architecture for various data sets.
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Manta, Otilia. "Financing and Fiscality in the Context of Artificial Intelligence at the Global Level". European Journal of Marketing and Economics 3, n.º 1 (1 de enero de 2020): 31. http://dx.doi.org/10.26417/ejme.v3i1.p31-47.
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The current financing models, as well as the fiscal models, are based on the current resources available at both the financial system and the fiscal system, but in close interdependence with those existing at the global level, the technology being one of them. Moreover, we consider that increasingly in the resource hierarchy, the place of the human factor is replaced by artificial intelligence (regardless of whether we are talking about industrial robots or intelligent technologies as is the case in the banking financial field). The new ways of approaching and coordinating finances aim to increase the degree of flexibility of financial networks and harmonize the results of those financial institutions that master and use complex but complementary technologies in order to obtain a final product or services optimal and with direct connection to its beneficiary. The defining elements for any financing and control model, regardless of whether we think of Fintech or other programs such as Fiscalis , are given by the following characteristics: digitization (artificial intelligence tools are crucial for digitizing financial services and fiscal), mobilization (virtual space offers not only the possibility but especially the platform for achieving the mobility of services), disintermediation (virtual space offers the possibility of direct access without intermediaries) and automation (through the financial services existing on the online platforms, the beneficiary of the service and the service provider optimizes its time and cost in favor of making the service profitable).
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Kefalas, Achilles, Andreas B. Ofner, Gerhard Pirker, Stefan Posch, Bernhard C. Geiger y Andreas Wimmer. "Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting". Sensors 22, n.º 11 (1 de junio de 2022): 4235. http://dx.doi.org/10.3390/s22114235.
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An optimal control of the combustion process of an engine ensures lower emissions and fuel consumption plus high efficiencies. Combustion parameters such as the peak firing pressure (PFP) and the crank angle (CA) corresponding to 50% of mass fraction burned (MFB50) are essential for a closed-loop control strategy. These parameters are based on the measured in-cylinder pressure that is typically gained by intrusive pressure sensors (PSs). These are costly and their durability is uncertain. To overcome these issues, the potential of using a virtual sensor based on the vibration signals acquired by a knock sensor (KS) for control of the combustion process is investigated. The present work introduces a data-driven approach where a signal-processing technique, designated as discrete wavelet transform (DWT), will be used as the preprocessing step for extracting informative features to perform regression tasks of the selected combustion parameters with extreme gradient boosting (XGBoost) regression models. The presented methodology will be applied to data from two different spark-ignited, single cylinder gas engines. Finally, an analysis is obtained where the important features based on the model’s decisions are identified.
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Sriatmi, Ayun, Sri Suwitri, Zahroh Shaluhiyah y Sri Achadi Nugraheni. "Dapatkah Kelas Ibu Hamil Model Virtual Meningkatkan Praktik Pencegahan Risiko Tinggi Kehamilan ?" Media Penelitian dan Pengembangan Kesehatan 30, n.º 1 (31 de mayo de 2020): 1–14. http://dx.doi.org/10.22435/mpk.v30i1.2985.
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Abstract
The inability of pregnant women to identify and recognize danger signs of pregnancy indicates the lack of knowledge, attitudes and perceptions of mothers about healthy pregnancies which has an impact on the low practices of prevention of high risk of pregnancy. Pregnant Women Class Program (KIH) which is held is not optimal because of the low presence of pregnant women for various reasons. The aim of study to determine the effect of the KIH-Virtual model on the practice of preventing high risk of pregnancy. This is a quasi-experimental study with case-control approach. The population is pregnant women in Semarang City. The total sample was 60 mothers for the intervention group and 61 mothers for control group. The independent variable is KIH-Virtual intervention and dependent variable is the practice of preventing high risk pregnancy (covering 7 dimensions). Data collection through interviews and observations with four times measurements (pretest, posttest 1,2,3). Partial analysis using independent-T test and Paired test. Simultaneous analysis with Linear-Mixed-Model. Statistically, there were differences in the practice of preventing high risk pregnancy between intervention groups and control at the last measurement (p<0.05). Although both groups experienced an increase in scores at each measurement stage, it was evident in the intervention group that the increase was higher for all dimensions of practice. The highest increase in the effect of interventions on communication and collaboration practices was followed by health status monitoring practices. Daily self-care practices and lifestyle practices are the dimensions with the lowest intervention effect. Virtual-KIH influences the practice of pregnant women in the prevention of high risk of pregnancy and is able to improve the practice better than conventional models that have been underway.
Abstrak
Ketidakmampuan ibu hamil mengidentifikasi dan mengenali tanda bahaya kehamilan mengindikasikan rendahnya pengetahuan, sikap dan persepsi ibu tentang kehamilan sehat, yang berdampak pada rendahnya praktik pencegahan risiko tinggi kehamilan. Program Kelas Ibu Hamil (KIH) yang diselenggarakan belum optimal karena terkendala rendahnya kehadiran ibu hamil dengan berbagai alasannya. Tujuan penelitian menganalisis pengaruh model KIH Virtual terhadap praktik pencegahan risiko tinggi kehamilan. Penelitian ini merupakan penelitian quasi experimental dengan pendekatan kasus-kontrol. Populasi adalah ibu hamil di Kota Semarang. Jumlah sampel 60 ibu untuk kelompok intervensi dan 61 ibu untuk kelompok kontrol. Variabel bebas yaitu intervensi KIH Virtual dan variabel terikatnya yaitu praktik pencegahan risiko tinggi kehamilan (meliputi 7 dimensi). Pengumpulan data melalui wawancara dan observasi dengan 4 kali pengukuran (pretest, posttest-1,2,3). Analisis parsial menggunakan uji beda independen dan berpasangan. Analisis simultan dengan Linear-Mixed-Model. Secara statistik ada perbedaan praktik pencegahan risiko tinggi kehamilan antara kelompok intervensi dengan kontrol pada pengukuran terakhir (p<0,05). Meski kedua kelompok mengalami peningkatan skor pada setiap tahap pengukuran, namun terbukti pada kelompok intervensi peningkatannya lebih tinggi untuk semua dimensi praktik. Peningkatan tertinggi efek intervensi pada praktik komunikasi dan kerjasama, diikuti praktik pemantauan status kesehatan. Praktik perawatan diri sehari-hari dan praktik gaya hidup merupakan dimensi praktik dengan efek intervensi terendah. KIH Virtual memengaruhi praktik ibu hamil dalam pencegahan risiko tinggi kehamilan dan mampu meningkatkan praktik tersebut dengan lebih baik dibandingkan model konvensional yang selama ini berlangsung.
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Jo, Hanjin, Woong Choi, Geonhui Lee, Wookhyun Park y Jaehyo Kim. "Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration". Sensors 20, n.º 21 (8 de noviembre de 2020): 6368. http://dx.doi.org/10.3390/s20216368.
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The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human–robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominant hands in tracking a target in the three-dimensional space. We compared the circular tracking performances of the hands on the frontal plane of the virtual reality space in terms of radial position error (ΔR), phase error (Δθ), acceleration error (Δa), and dimensionless squared jerk (DSJ) at four different speeds for 30 subjects. ΔR and Δθ significantly differed at relatively high speeds (ΔR: 0.5 Hz; Δθ: 0.5, 0.75 Hz), with maximum values of ≤1% compared to the target trajectory radius. DSJ significantly differed only at low speeds (0.125, 0.25 Hz), whereas Δa significantly differed at all speeds. In summary, the feedback-control mechanism of the DH has a wider range of speed control capability and is efficient according to an energy saving model. The central nervous system (CNS) uses different models for the two hands, which react dissimilarly. Despite the precise control of the DH, both hands exhibited dependences on limb kinematic properties at high speeds (0.75 Hz). Thus, the CNS uses a different strategy according to the model for optimal results.
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Funes, Estrella, Yosra Allouche, Gabriel Beltrán, M. Paz Aguliera y Antonio Jiménez. "A predictive artificial neural network model as a simulator of the extra virgin olive oil elaboration process". Journal of Near Infrared Spectroscopy 25, n.º 4 (agosto de 2017): 278–85. http://dx.doi.org/10.1177/0967033517725639.
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Nine neural models were created to predict the characteristics of the extra virgin olive oil developed as a quality objective and by-products. These models are designed with the help of data of process variables from physical sensors such as temperature, flows, current intensity, etc. and physicochemical ones like the near infrared spectrum of the olive mass. The results obtained for the extractability of the process (fatty content and moisture) were highly significant correlations (r2≥0.90) and with similar prediction errors (root mean of squared error of prediction) relative to other analysis techniques which measure the by-product directly. For prediction the models gave correlations above 0.94, with the exception of ultraviolet absorption coefficients (0.72–0.84), with small prediction errors and the quality indicator relative error range with values above the optimal 10. The set of developed artificial neural networks models constitute the basis of the global ‘simulator’ tool of the extra virgin olive oil process. This simulator can perform a predictive optimization of the process to pre-adjust the process variables according to the goals marked in productivity or quality, from an near infrared spectral database or by real-time scanning. This simulator could be integrated into a control system that performs the function of a ‘virtual plant’ that allows the said system to adjust in real time the appropriate variables to meet the objectives.
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Gaska, Krzysztof y Agnieszka Generowicz. "SMART Computational Solutions for the Optimization of Selected Technology Processes as an Innovation and Progress in Improving Energy Efficiency of Smart Cities—A Case Study". Energies 13, n.º 13 (30 de junio de 2020): 3338. http://dx.doi.org/10.3390/en13133338.
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The paper presents advanced computational solutions for selected sectors in the context of the optimization of technology processes as an innovation and progress in improving energy efficiency of smart cities. The main emphasis was placed on the sectors of critical urban infrastructure, including in particular the use of algorithmic models based on artificial intelligence implemented in supervisory control systems (SCADA-type, including Virtual SCADA) of technological processes involving the sewage treatment systems (including in particular wastewater treatment systems) and waste management systems. The novelty of the presented solution involves the use of predictive diagnostic tools, based on multi-threaded polymorphic models supporting decision making processes during the control of a complex technological process and objects of distributed network systems (smart water grid, smart sewage system, smart waste management system) and solving problems of optimal control for smart dynamic objects with logical representation of knowledge about the process, the control object and the control itself, for which the learning process consists of successive validation and updating of knowledge and the use of the results of this updating to make control decisions. The advantage of the proposed solution in relation to the existing ones lies in the use of advanced models of predictive diagnostics, validation and reconstruction of data, implemented in functional tools, allowing the stabilization of the work of technological objects through the use of FTC technology (fault tolerant control) and soft sensors, predictive measurement path diagnostics (sensors, transducers), validation and reconstruction of measurement data from sensors in the measuring paths in real time. The dedicated tools (Intelligent Real Time Diagnostic System − iRTDS) built into the system of a hierarchical, multi-threaded control optimizing system of SCADA system allow to obtain advanced diagnostics of technological processes in real time using HPC technology. In effect of the application of the proprietary iRTDS tool, we obtain a significant rise of energy efficiency of technological processes in key sectors of the economy, which in global terms, e.g., urban agglomeration, increases the economic efficiency.
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Ramos, Helena M., Maria Cristina Morani, Armando Carravetta, Oreste Fecarrotta, Kemi Adeyeye, P. Amparo López-Jiménez y Modesto Pérez-Sánchez. "New Challenges towards Smart Systems’ Efficiency by Digital Twin in Water Distribution Networks". Water 14, n.º 8 (17 de abril de 2022): 1304. http://dx.doi.org/10.3390/w14081304.
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Nowadays, in the management of water distribution networks (WDNs), particular attention is paid to digital transition and the improvement of the energy efficiency of these systems. New technologies have been developed in the recent years and their implementation can be crucial to achieve a sustainable level of water networks, namely, in water and energy losses. In particular, Digital Twins (DT) represents a very innovative technology, which relies on the integration of virtual network models, optimization algorithms, real time data collection, and smart actuators information with Geographic Information System (GIS) data. This research defines a new methodology for an efficient application of DT expertise within water distribution networks. Assuming a DMA of a real water distribution network as a case study, it was demonstrated that a fast detection of leakage along with an optimal setting of pressure control valves by means of DT together with an optimization procedure can ensure up to 28% of water savings, contributing to significantly increase the efficiency of the whole system.