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Energy-efficient virtual sensor-based deep reinforcement learning control of indoor CO_(2)in a kindergarten

Frontiers of Architectural Research 2023年第2期12卷 394-409页

作者： Patrick Nzivugira Duhirwe Jack Ngarambe Geun Young Yun Department of Architectural Engineering Kyung Hee UniversityYongin 17104Republic of Korea

High concentrations of indoor CO_(2)pose severe health risks to building ***,mechanical equipment is used to provide sufficient ventilation as a remedy to high indoor CO_(2)***,such equipment consumes large amounts of energy,substantially increasing building energy *** the end,the issue becomes an optimization problem that revolves around maintaining CO_(2)levels below a certain threshold while utilizing the minimum amount of energy *** that end,we propose an intelligent approach that consists of a supervised learning-based virtual sensor that interacts with a deep reinforcement learning(DRL)-based control to efficiently control indoor CO_(2)while utilizing the minimum amount of energy *** data used to train and test the DRL agent is based on a 3-month field experiment conducted at a kindergarten equipped with a heat recovery *** results show that,unlike the manual control initially employed at the kindergarten,the DRL agent could always maintain the CO_(2)concentrations below sufficient ***,a 58%reduction in the energy consumption of the ventilator under the DRL control compared to the manual control was *** demonstrated approach illustrates the potential leveraging of Internet of Things and machine learning algorithms to create comfortable and healthy indoor environments with minimal energy requirements.

关键词： Indoor air quality Indoor CO_(2)control Machine learning virtual sensor Deep reinforcement learning

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Wear dependent virtual flow rate sensor for progressing cavity pumps with deformable stator

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Petroleum Science 2024年第2期21卷 1346-1353页

作者： Jens Müller Sebastian Leonow Johannes Schulz Christian Hansen Martin Monnigmann Ruhr-Universitat Bochum Universit atsstraûe 150Bochum44801Germany SEEPEX GmbH Scharnh olzstraûe 344Bottrop46240Germany

This contribution presents a novel wear dependent virtual flow rate sensor for single stage single lobe progressing cavity pumps. We study the wear-induced material loss of the pump components and the impact of this material loss on the volumetric efficiency. The results are combined with an established backflow model to implement a backflow calculation procedure that is adaptive to wear. We use a laboratory test setup with a highly abrasive fluid and operate a pump from new to worn condition to validate our approach. The obtained measurement data show that the presented virtual sensor is capable of calculating the flow rate of a pump being subject to wear during its regular operation.

关键词： Backflow Progressing cavity pump virtual sensor Wear

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Innovative Services for Electric Mobility Based on virtual sensors and Petri Nets

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1845-1859页

作者： Agostino Marcello Mangini Michele Roccotelli Department of Electrical and Information Engineering Polytechnic University of BariBari 70126Italy

About 60%of emissions into the earth’s atmosphere are produced by the transport sector,caused by exhaust gases from conventional internal combustion *** effective solution to this problem is electric mobility,which significantly reduces the rate of urban *** use of electric vehicles(EVs)has to be encouraged and facilitated by new information and communication technology(ICT)*** help achieve this goal,this paper proposes innovative services for electric vehicle users aimed at improving travel and charging *** goal is to provide a smart service to allow drivers to find the most appropriate charging solutions during a trip based on information such as the vehicle’s current position,battery type,state of charge,nearby charge point availability,and *** particular,the drivers are supported so that they can find and book the preferred charge option according to time availability and the final cost of the charge points(CPs).To this purpose,two virtual sensors(VSs)are designed,modeled and simulated in order to provide the users with an innovative service for smart CP searching and *** particular,the first VS is devoted to locate and find available CPs in a preferred area,whereas the second VS calculates the charging cost for the EV and supports the driver in the booking phase.A UML activity diagram describes VSs operations and cooperation,while a UML sequence diagram highlights data exchange between the VSs and other electromobility ecosystem actors(CP operator,EV manufacturer,etc.).Furthermore,two timed Petri Nets(TPNs)are designed to model the proposed VSs,functioning and interactions as discrete event *** Petri Nets are synchronized by a single larger TPN that is simulated in different use cases and scenarios to demonstrate the effectiveness of the proposed VSs.

关键词： Charge point booking electric mobility EV charging Petri Net virtual sensor

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A Machine Learning Based Method of Constructing virtual Inertial Measurement Predictor of Human Body

A Machine Learning Based Method of Constructing Virtual Iner...

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第36届中国控制会议

作者： QIAN Weixing LI Rongbing XIE Fei LUO Haonan WANG Yuntao ZHENG Tingting School of Electrical and Automation Engineering Nanjing Normal University College of Automation Nanjing University of Aeronautics and Astronautics

In recent years,using human characteristics to assist exoskeleton robot control is one of the hot spots in the field of robot *** the problem that extremity installation of inertial measurement components in human body cannot achieve effective measurement,a method of constructing virtual inertial measurement predictor of human body based on machine learning is *** method uses the outputs of the inertial measurement components synchronously installed on the extremities and other parts of the body as the data samples,through recurrent neural network,it realizes the construction of virtual inertial measurement components and their *** order to improve the training effect,the training samples are filtered based on gait phase *** simulation based on Anybody and MATLAB shows that,by installing the inertial measurement component near hip joint,the proposed method can effectively simulate and predict the inertial measurement component’s output of centroid position of foot and surface of shank.

关键词： Kinematic model of human body virtual sensor Machine learning Gait detection Motion prediction

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Research on the Control Architecture of Teleoperation Based on Intelligent Sensing Network

Research on the Control Architecture of Teleoperation Based ...

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2001 International Conferences on Info-tech and Info-net

作者： Jianjun Zhang Yunjian Ge Department of Automation University of Science and Technology Institute of Intelligent Machines Chinese Academy of Sciences

＜正＞With the rapid development of intelligent sensor/actuator and network technology,more and more researchers have realized the necessity to acquire,transmit and process sensing data through wide area network（such as Internet） in order to improve the stability,reliability and real-time performance of present teleoperation ***,the combination of these two technologies has become a very important aspect in the study scope of intelligent sensor/*** paper mainly discusses a novel control architecture approach of teleoperation based on intelligent sensing *** also discusses several key problems and corresponding solution in this regard.

关键词： control architecture intelligent sensing network virtual sensor soft sensor teleoperation

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