scholarly journals A scheduling and control integration optimization method for regenerative braking energy utilization

2021 ◽  
Vol 336 ◽  
pp. 02018
Author(s):  
Shunyao Yang ◽  
Xubin Sun
Keyword(s):  
Energy Saving ◽  
Real Data ◽  
Optimization Method ◽  
Energy Utilization ◽  
Regenerative Braking ◽  
Random Disturbance ◽  
The Real ◽  
Scheduling Optimization Algorithm ◽  
And Control ◽  
Control Integration

The utilization of regenerative braking energy is of great significance to the energy saving of subway. Therefore, this paper proposes an optimization method for scheduling and control integration, which not only adjusts the timetable but also optimizes the speed curves of trains. When there is a train braking, this method will try to find a train that accelerates to absorb the regenerative energy generated by the braking train. Firstly, this paper establishes the timetable energy saving optimization model, based on which the speed curves will be optimized. Furthermore, we design a scheduling optimization algorithm based on genetic algorithm, and optimizes speed curves of trains by binary search method to obtain a good solution. Finally, simulations are given using the real data of Beijing Metro Line 4 to evaluate the proposed method, and the results show that the integrated scheduling and control optimization method can reduce energy consumption by 15.18%. In the random disturbance simulations, the proposed method shows good robustness, which makes it possible to apply this method to the real subway operations.

On the Control of the Collector Field Outlet Temperature of Shiraz 250 KW Solar Power Plant

2012 ◽  
Vol 260-261 ◽  
pp. 163-168 ◽  
Author(s):  
Mostafa Zamani Mohi Abadi ◽  
Seyed Mohammad Hessam Mohammadi ◽  
Seyed Ali Akbar Safavi ◽  
Seyed Vahid Naghavi
Keyword(s):  
Power Plant ◽  
Solar Power ◽  
Real Data ◽  
Outlet Temperature ◽  
Solar Power Plant ◽  
Modeling And Control ◽  
The Real ◽  
Standard Tool ◽  
And Control ◽  
Control Study

This paper presents a control study of the real Shiraz 250KW solar power plant together with a modeling and a monitoring interface. Here, a PID controller is developed to control the outlet oil temperature of the collector field of the solar power plant as a standard tool for industrial automation. First the power plant is modeled within MATLAB environment and the model is verified with the real data of the power plant. Then an HMI environment is developed within the LabVIEWsoftwarewhile incorporating the model developed in MATLAB. The simulation results showed that a fixed-coefficient PID failed to provide the desired results over a year and the best coefficients for each month were calculated. The friendly and accurate developed environment within MATLAB and LabVIEW provide a valuable tool for modeling and control studies and monitoring of the real power plant.

scholarly journals Comparison Of Modeling Schemes for Natural Course Of Pulmonary Tuberculosis

2019 ◽  
Vol 14 (2) ◽  
pp. 570-587 ◽  
Author(s):  
K.K. Avilov ◽  
A.A. Romanyukha ◽  
E.M. Belilovsky ◽  
S.E. Borisov
Keyword(s):  
Pulmonary Tuberculosis ◽  
Real Data ◽  
Health Condition ◽  
Natural Course ◽  
The Real ◽  
Moscow City ◽  
History Of ◽  
The Moment ◽  
And Control ◽  
Incident Cases

In construction of mathematical models of propagation and control of pulmonary tuberculosis, presence or absence of bacterioexcretion is often used as the marker of disease severity. There are two major schemes of modeling for natural corse of tuberculosis. The first one is so called parallel scheme, the more frequently used, which assumes that a fraction of incident cases develops bacterioexcretion rapidly and retains it till the end of the disease. The second one is serial scheme, the less often used one, which assumes that tuberculosis always starts without bactrioexcretion, and then a fraction of cases progresses to the bacterioexcretion stage. In this article, we compare these two modeling schemes on the basis of their fit to the real data from Moscow city, 2013-2018, which contain information on time and results of the last fluorography examination of the detected tuberculosis cases and their health condition at the moment of detection. Such data limit the possible duration of the disease, and, thus, permit an estimation of the dynamics of progression to bacterioexcretion for untreated tuberculosis. We have developed an agent-based model with realistic profiles of mortality and undergoing fluorography examinations and with an analog of the traditional compartmental model of natural history of tuberculosis on the basis of ordinary differential equations. On the basis of computational experiments with the model, the serial modelling scheme turned out to be closer to reality. On the other hand, due to the bad fit to the real data, we concluded that both the detection submodel and the submodel of natural course of pulmonary tuberculosis should be redesigned.

scholarly journals Research on Modeling and Control of Regenerative Braking for Brushless DC Machines Driven Electric Vehicles

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Jian-ping Wen ◽  
Chuan-wei Zhang
Keyword(s):  
Control Method ◽  
Mathematic Model ◽  
Energy Utilization ◽  
Regenerative Braking ◽  
Utilization Rate ◽  
Modeling And Control ◽  
Brushless Dc ◽  
Braking System ◽  
Unknown Disturbances ◽  
And Control

In order to improve energy utilization rate of battery-powered electric vehicle (EV) using brushless DC machine (BLDCM), the model of braking current generated by regenerative braking and control method are discussed. On the basis of the equivalent circuit of BLDCM during the generative braking period, the mathematic model of braking current is established. By using an extended state observer (ESO) to observe actual braking current and the unknown disturbances of regenerative braking system, the autodisturbances rejection controller (ADRC) for controlling the braking current is developed. Experimental results show that the proposed method gives better recovery efficiency and is robust to disturbances.

Single Depth View Based Real-Time Reconstruction of Hand-Object Interactions

2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu
Keyword(s):  
Real Time ◽  
Synthetic Data ◽  
Real Data ◽  
Depth Image ◽  
Real Time System ◽  
The Real ◽  
Time Performance ◽  
Contact Constraint ◽  
Object Shapes ◽  
Object Interactions

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.

scholarly journals A fractional order epidemic model for the simulation of outbreaks of Ebola

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Weiqiu Pan ◽  
Tianzeng Li ◽  
Safdar Ali
Keyword(s):  
Numerical Solution ◽  
Root Mean Square ◽  
Fractional Order ◽  
Relative Error ◽  
Numerical Solutions ◽  
Real Data ◽  
Mean Square ◽  
Order Model ◽  
The Real ◽  
Fractional Orders

AbstractThe Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number $R_{0}$ R 0 , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error $g(U^{*})=0.4146$ g ( U ∗ ) = 0.4146 are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is $g(U^{*})=0.2744$ g ( U ∗ ) = 0.2744 . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data.

Petrophysical Facies Classification Based on Fuzzy Inference Networks

2013 ◽  
Vol 634-638 ◽  
pp. 4017-4021
Author(s):  
Jun Hui Pan ◽  
Hui Wang ◽  
Xiao Gang Yang
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Reasoning ◽  
Real Data ◽  
Analysis Data ◽  
Classification Model ◽  
Core Analysis ◽  
Development Zone ◽  
The Real ◽  
Facies Classification ◽  
Quantitative Indicators

Aiming at the petrophysical facies recognition, a novel identification method based on the weighted fuzzy reasoning networks is proposed in the paper. First, the types and indicators are obtained from core analysis data and the results given by experts, and then the standard patterning database of reservoir petrophysical facies is established. Secondly, by integrating expert experiences and quantitative indicators to reflect the change of petrophysical facies, the classification model of petrophysical facies based on the weighted fuzzy reasoning networks is designed. The preferable application results are presented by processing the real data from the Sabei development zone of Daqing oilfield.

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