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检索条件"任意字段=Conference on Advanced Process Control and Automation"

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Enhancing Urban Water Distribution: The Role of Automated Systems and PLC Applications

Enhancing Urban Water Distribution: The Role of Automated Sy...

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Modeling, Simulation & Intelligent Computing (MoSICom), International conference on

作者： Abdul Azeez Ashique Ashton Rebello Ganesan Subramanian Naveen Chandrasekar dept. of Mechatronics engineering Manipal academy of higher education Dubai United Arab Emirates dept of computer studies Symbiosis International University Dubai. Manipal academy of higher education Dubai United Arab Emirates

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

Due to the increase in population accompanied by the expansive growth of urban residential areas, the demand for efficient and reliable water distribution systems has increased rapidly. And as urbanisation increases day by day this demand for water is equal to the need for sustainable water management and distribution systems. Thus, it becomes an utmost necessity for the implementation of proper controlling and monitoring mechanisms to prevent wastage of water and also attempts of water theft. As a solution to these challenges, many advanced technologies have been identified all over the world to ensure effective distribution of water to reach every household especially in urban areas. Therefore, my paper estimates and understands the current state of automated water distribution systems with a prime focus on monitoring performance and control through PLC (programmable logic controller) applications. In the initial areas of this paper, it focuses on the basic concept of automatic water distribution that has been implemented in the current scenario in urban areas. This study includes thorough research on the details of the system, how it is operated, its principles, and intended functions. The next stage of research will be focussed on a comparative analysis of various technologies that have been studied and implemented in the field of automated water distribution. This paper shows key innovations, challenges and future goals in the realm of automated water distribution. It also shows the possibility for the integration of PLC systems, discussing how efficiently these systems contribute to the optimization of the water distribution process. Thus, proving PLC systems plays a crucial role in improving the overall performance and sustainability of water distribution systems by monitoring real-time data.

关键词： Technological innovation automation Urban areas control systems Hardware Software Software reliability Sustainable development Water resources Monitoring

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Low-Carbon Optimization Dispatch of Multi-Integrated Energy System Based on Kriging Metamodel and Stackelberg Game

Low-Carbon Optimization Dispatch of Multi-Integrated Energy ...

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IEEE PES Asia-Pacific Power and Energy Engineering conference (APPEEC)

作者： Zhaoqing Zhang Yonghui Sun Fan Sheng Chenxu Yin Denis N. Sidorov Alexey B. Iskakov School of Electrical and Power Engineering Hohai University Nanjing China Melentiev Energy System Institute Russian Academy of Sciences Irkutsk Russia School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Trapeznikov Institute of Control Sciences Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

Integrated energy system (IES) is an advanced configuration that combines electrical energy, thermal energy, and renewable energy, into a unified system. In recent years, the architecture of IES has gradually changed from vertical integration to interactive competition, and its distributed characteristics have become increasingly evident. Therefore, traditional centralized optimization strategies can no longer meet the current practical situation. In this paper, a low-carbon optimization dispatch for IES based on Stackelberg game and kriging metamodel is proposed. In order to address this problem, firstly, three typical models containing hydrogen blending gas technology and a kind of ladder-type carbon trading mechanism considering reward and punishment (RP-LCTM) are established. Secondly an integrated energy manager (IEM) is introduced and a Stackelberg game model with the IEM as the leader and three typical IESs as followers is established. Finally, the kriging metamodel is used to optimize the transaction electricity price. During the game process, the IPSO algorithm is used to optimize electricity prices in key price regions. At last, an experimental example is utilized to demonstrate the effectiveness of the proposed method.

关键词： Renewable energy sources Electricity Hydrogen Fitting Games Emissions trading Optimal scheduling Optimization Thermal energy

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An IoT Sensor Node SoC with Dynamic Power Scheduling for Sustainable Operation in Energy Harvesting Environment

An IoT Sensor Node SoC with Dynamic Power Scheduling for Sus...

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IEEE Asian conference on Solid-State Circuits (ASSCC)

作者： Yuji Yano Seiya Yoshida Shintaro Izumi Hiroshi Kawaguchi Tetsuya Hirose Masaya Miyahara Teruki Someya Kenichi Okada Ippei Akita Yoshihiko Kurui Hideyuki Tomizawa Masahiko Yoshimoto Graduate School of System Informatics Kobe University Kobe Japan Graduate School of Engineering Osaka University Osaka Japan High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki Japan School of Engineering Tokyo Institute of Technology Tokyo Japan Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan Corporate R&D Center Toshiba Corporation Kanagawa Japan

ISBN: (数字)9781728151069

ISBN: (纸本)9781728151076

This paper describes a low-power IoT sensor node SoC that can be used for factory automation and wearable healthcare applications. It features dynamic power scheduling method suitable for the environment that works with an energy harvester. Our proposed SoC architecture is composed of a low power (60 nA) RTC, a normally-off RF which has fast start-up time (0.5 μs), and other low-power components. A mixed-signal SoC has been fabricated using the TSMC 65 nm LP process. The sensor node system equipped with dynamic power scheduling consumes about 3.4 μW when the activity ratio is 0.1%. Evaluation results show that the proposed method can reduce about 51% of the power consumption compared with the case without dynamic power scheduling in sensor node SoC. Also, the parameters of the system in energy harvesting environment can be adjusted under the trade-off with power consumption and measurement accuracy according to the application requirements.

关键词： Dynamic scheduling Clocks Voltage control Random access memory Power demand Sensors

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Communication test and analysis of integrated protection system in digital substation

Communication test and analysis of integrated protection sys...

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2011 International conference on advanced Power System automation and Protection(APAP 2011)

作者： WU TingTing, WANG Bin, DONG XinZhou, SHI ShenXing, ZHOU YunHai, LIU Kun, YANG YueLin School of Electrical Engineering & Renewable Energy, China Three Gorges University, Yichang 443000, China State Key Lab of control and Simulation of Power Systems and Generation Equipments, Dept. of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China College Of Information and Electrical Engineering, CHINA Agricultural University, Haidian District, Beijing 100083, China

The development of digital substation provides new opportunity for integrated protection. However, the realization of integrated protection is constrained by serial communication between process level and bay level. Based on developed digital integrated protection and control system platform, the result of a physical simulation test concerning communication system reveals the problem of communication instability and packet loss. In this paper, the impact of GPS exerted on stability of integrated protection is tested and analyzed. Without GPS time setting of Merging Unit(MU) in different bay, the integrated protection system will lose data in one minute after running. With GPS, the communication is stable and reliable, but the time interval between two packets in a cycle is quite long. Since sampling of MU in different bay is synchronized by GPS, the availability of integrated protection system is directly affected by communication of integrated protection in digital substation.

关键词： DM9000, ARM, GPS, packet loss

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Extended Reality for Enhanced Human-Robot Collaboration: a Human-in-the-Loop Approach

Extended Reality for Enhanced Human-Robot Collaboration: a H...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Yehor Karpichev Todd Charter Jayden Hong Amir M. Soufi Enayati Homayoun Honari Mehran Ghafarian Tamizi Homayoun Najjaran Advanced Control and Intelligent Systems Laboratory (ACIS) University of Victoria Victoria Canada

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-robot collaboration attempts to tackle these challenges by combining the strength and precision of machines with human ingenuity and perceptual understanding. In this paper, we conceptualize and propose an implementation framework for an autonomous, machine learning-based manipulator that incorporates human-in-the-loop principles and leverages Extended Reality (XR) to facilitate intuitive communication and programming between humans and robots. Furthermore, the conceptual framework foresees human involvement directly in the robot learning process, resulting in higher adaptability and task generalization. The paper highlights key technologies enabling the proposed framework, emphasizing the importance of developing the digital ecosystem as a whole. Additionally, we review the existent implementation approaches of XR in human-robot collaboration, showcasing diverse perspectives and methodologies. The challenges and future outlooks are discussed, delving into the major obstacles and potential research avenues of XR for more natural human-robot interaction and integration in the industrial landscape.

关键词： Manufacturing processes Extended reality Reviews Ecosystems Human-robot interaction Programming Manipulators Human in the loop Robot learning Machinery

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Data Augmented Deep Reinforcement Learning for Online 3D Bin Packing Problems

Data Augmented Deep Reinforcement Learning for Online 3D Bin...

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第43届中国控制会议

作者： Xuanye Zhang Yunwen Xu Dewei Li Department of Automation Shanghai Jiao Tong University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

With the rapid expansion of the logistics industry, the bin packing problem(BPP) has become an increasingly popular area of research due to its extensive applications in conveyor belt systems and warehouse scenarios. As a typical NP-hard combinatorial optimization problem, previous researchers designed various heuristic algorithms. Recent prosperity in deep reinforcement learning(DRL) also brings new insight to the operation research community. However, the performance of heuristic searching is mediocre while learning-based methods are often hard to train and lack interpretability. Simultaneously, most of the methods have employed discretized modeling for bins and items, further constraining the applicability of packing algorithms in continuous real-world scenarios. This paper presents a heuristic-guided DRL framework to solve online BPP. The proposed method adopts an inherited tree structure to represent the state and the packing agent is trained with an advanced value-based DRL algorithm. Besides, a novel data augmentation technique suitable for BPP is designed to accelerate the training process and reduce the computational burden. Extensive experiments are conducted on both discrete and continuous scenarios for training and evaluation. The proposed method achieves state-of-the-art(SOTA) performance on particular benchmark problem *** effectiveness of our method in solving online BPPs is confirmed by its superiority over existing works.

关键词： Deep Reinforcement Learning Combinatorial Optimization Bin Packing Problem Data Augmentation

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Integrating GNSS and INS Data with Deep Learning-Enhanced Invariant Extended Kalman Filter for Train Localization

Integrating GNSS and INS Data with Deep Learning-Enhanced In...

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第43届中国控制会议

作者： Zheyu Sun Haifeng Song Min Zhou Hao Yin Hairong Dong School of Automation and Intelligence Beijing Jiaotong University School of Electronic and Information Engineering Beihang University College of Electrical Engineering and Automation Shandong University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Ensuring precise train localization is crucial for the operational safety and efficiency of railway networks. Conventional localization techniques face limitations due to dynamic environmental noise, impacting the accuracy of such systems. In response, this study proposes a sophisticated approach that incorporates a deep learning-enhanced Invariant Extended Kalman Filter, utilizing a Convolutional Neural Network-Long Short-Term Memory(CNN-LSTM) architecture. This innovative method dynamically adjusts the noise parameters within the Kalman filtering process. The CNN component extracts spatial features,while the LSTM module analyzes temporal sequences, thereby optimizing the filter's performance under varying environmental conditions. The integration of Global Navigation Satellite System(GNSS) and Inertial Navigation System(INS) data forms the core of our investigation, addressing the complexities inherent in train localization tasks. Rigorous evaluations on real-world datasets have demonstrated a notable enhancement in localization accuracy, achieving a [specific improvement percentage] over conventional Kalman filter methods. The outcomes of this research underscore the transformative impact of deep learning on railway system advancements and set a foundation for subsequent innovations in intelligent transportation systems. By merging advanced deep learning algorithms with traditional signal processing, our work contributes to the evolution of more dependable and efficient train localization solutions, paving the way for future developments in this critical area of intelligent transportation systems.

关键词： Invariant Extended Kalman Filter Deep Learning Optimization Train Localization GNSS/INS Data Fusion

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RGB-D Instance Segmentation-based Suction Point Detection for Grasping

RGB-D Instance Segmentation-based Suction Point Detection fo...

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IEEE International conference on Robotics and Biomimetics

作者： Yeyu Fu Ting Sun Li Wang Shijie Yu Lei Deng Baohua Chen Lin Li Yusen Xie Shuixin Deng Hanxi Yin Joint International Research Laboratory of Advanced Photonics and Elextronics Beijing Information Science & Technology University Beijing China Department of Perception zhong-guancun Open Lab. Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control Engineering Beijing China Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9781665481106

Suction is a common way for robots to pick objects in industry, which has higher stability and reliability. However, it is necessary to evaluate the suction position on the object's surface when dealing with objects of different shapes. The previous method decouples it into a two-stage suction point detection and objects classification process, making the task more complex and time-consuming. On the other hand, there are significant challenges in acquiring training data. To address that, we propose an object instance segmentation-based suction grasping point detection method. Instance segmentation, as an object pixel-level perception method, can classify objects and find the orientation of objects in the plane, which is more efficient than simple classification. Specifically, our method generate a suction heatmap and object instance segmentation from RGB-D inputs and find the suction grasping position of each object after candidate points screening. To generate the training data, a heatmap mask based on 2D Gaussian-encoded is used to annotate the suction grasping ground truth. We evaluate each object's predicted suction grasping point results and conduct grasping experiments in real environments. The suction grasping success rate of 94% in dense scenes demonstrates the remarkable performance of the proposed method.

关键词： Heating systems Shape Service robots Design methodology Training data Grasping Stability analysis

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A fluid dynamic analysis in the chamber and nozzle for a jetting dispenser design

A fluid dynamic analysis in the chamber and nozzle for a jet...

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2010 11th International conference on Electronic Packaging Technology & High Density Packaging(2010 电子封装技术与高密度封装国际会议)

作者： Haili Jia Jinsong Zhang Jianhua Zhang School of Mechatronics Engineering and Automation Shanghai University Shanghai City Key Laboratory of Advanced Display and System Applications of Ministry of Education Shanghai Univer

Electronic packaging industry widely uses a dispensing technology to deliver adhesive materials on substrates through a dispensing system. The cured adhesives can encapsulate and connect chips and substrates to provide mechanical, physical and chemical protections. For the high density packaging, a jet dispensing is regarded as the next generation adhesive delivery technology due to its features of non-contact, high precision and high efficiency. We developed a jet dispensing system including a jetting dispenser, a 3-axis movement platform, a substrate carrier, a power module, motion control hardware and software, supplementary modules, etc. The jetting dispenser is the most part since it affects the accuracy and quality during the dispensing process. Before its structure design and prototype manufacturing some important physical parameters can be determined by the fluid dynamics analysis. In the jetting dispenser, a piston drives a needle to move downwards and push the fluid flowing in the chamber and dispensing out of the nozzle. A simplified physical model has been set up to promote discussing the dynamic properties of the fluid. The results of dynamics analysis reveals that there are a back flow and a jetting flow existing in the chamber and an unsteady flow existing in the nozzle. The flow rate and volume are the most key parameters for the dispenser design. They are dependent on the nozzle length and diameter, the chamber length and diameter, the dynamic viscosity, the coefficient of the on-way resistance, the needle speed and the initial pressure on adhesive.

关键词： Needles Fluid dynamics Equations Mathematical model Substrates Force

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Error analysis of connection frame deformation considering magnetic force and thermal-structural coupling effects

Error analysis of connection frame deformation considering m...

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IEEE conference on Nanotechnology

作者： Lufan. Zhang Jiwen. Fang Zhili. Long Longsheng. Nian State Key Lab for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an China Shenzhen Key Lab for Advanced Motion Control and Modern Automation Equipments Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Dongguan Huazhong University of Science and Technology Manufacturing Engineering Institute Dongguan China

ISBN: (纸本)9781479956234

Connection frame has been a key module in a macro-micro platform. The error of connection frame deformation must be taken into account for nano-positioning motion in working process. While working, the nano-positioning motion is affected by the two major deformation error sources: magnetic force and thermal structural coupling effects. These error models were built by response surface method. Each experiment result can be obtained by calculation of finite element method. Their input variables of orthogonal experiment design were imported to the commercial software ANSYS to calculate and obtain output. The response surface model was built by the input and output data. Based on these models, change trends of deformation errors with design parameters can be revealed. And an optimal model of total deformations errors would be built. Finally, the minimum error of connection frame deformation considering magnetic force and thermal structural coupling effect was calculated by genetic algorithm. The optimal solutions were obtained when the total error iterate to 15 times as follows, D=32mm, L1=80mm, R=64mm. The improvement of deformation error considering magnetic force, thermal-structural coupling force and high acceleration is 86.48%, 0.26%, 26.85% These results can provide a more accurate prediction of error analysis in more widely used cases and also offer a theoretical support for improving nano-positioning accuracy of macro-micro platform.

关键词： Magnetic forces Acceleration Thermal force Couplings Force Optimization Deformable models

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