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23rd international conference on Control, automation and systems, ICCAS 2023

作者： Jeon, Jinwoo Jeong, Myungwoo Myung, Hyun School of Electrical Engineering KI-Robotics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

ISBN: (纸本)9788993215274

the quadruped robot has the advantage of having a high degree of freedom of motion. therefore, it has been used in various robot applications such as exploration. However, the quadruped robot is not easy to control due to the large number of joints. Existing control methodologies using proportional-integral-differential (PID) or model predictive control show decent performance on uniform terrain. However, the control performance is degraded in the extreme terrain where significant non-linear disturbance occurs. To tackle this problem, we propose FLONIC-Q: fuzzy logic and neural network-based intelligent control system for quadruped robots on extreme terrain. the proposed system includes high-level and low-level control using fuzzy logic and machine learning to deal with disturbances in extreme terrain. As demonstrated in the experiments, the proposed method performs superior to existing system response methods regarding absolute trajectory error and time analysis in various trajectory types. © 2023 ICROS.

关键词： Robot applications

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Energy-Saving Practice of Variable Frequency Drive Technology in Data Center HVAC System

Energy-Saving Practice of Variable Frequency Drive Technolog...

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international conference on Power and Energy Technology (ICPET)

作者： Chuanxian Ai Jinpeng Yang Rui Chen Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Branch The National Computer Network Emergency Response Technical Team/Coordination Center of China Kunming China Power Dispatch Control Center Guizhou Power Grid Co. Ltd. China Southern Power Grid Co. Ltd Guiyang China

the variable-frequency drive technology (VFD) can modify the motor speed or torque by varying the frequency and voltage of the AC motor input power according to the load demand as a way to save energy. To analyse the energy saving effect of variable-frequency drive technology applied to data centre heating, ventilation, and air conditioning (HVAC) systems, this paper applies VFD technology to data centre fluorine pump-compressor composite air conditioning systems, implements monitoring and analysis of the operational energy efficiency of this system before and after retrofit, and combines the actual application of this technology. the findings indicate that the VFD technology can substantially reduce the number of compressor starts and stops, reduce the compressor start-up inrush current, and improve the power system’s stability. Furthermore, utilising this technology, the HVAC system can effectively synchronise with the load and fluctuations in outdoor temperature and humidity, resulting in accurate temperature regulation and optimal utilisation of outdoor cooling resources. this approach can lead to significant energy conservation of up to 42.95% when compared to extreme hot and cold weather conditions. the findings of the study indicate that the utilisation of VFD technology exhibits commendable adaptability and yields favourable outcomes in regions with varying temperature ranges. the minimum PUE value recorded was 1.228.

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2019年第五届IEEE控制、自动化和机器人技术大会(ICCAR 2019)

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智能系统学报 2019年第2期14卷 223-223页

Over the past five years,we witnessed the world we live in entirely disrupted by improvements in artificial intelligence(AI),machine learning and control *** and machine learning are trading millions of dollars in financial markets;they are predicting what people want to search for online;facial recognition helps police identify criminals.

关键词： AI ICCAR 2019

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Condition monitoring for the quadruple water tank system using H-infinity Kalman Filtering 5

Condition monitoring for the quadruple water tank system usi...

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5th international conference of Engineering Against Failure, ICEAF-V 2018

作者： Rigatos, Gerasimos Serpanos, Dimitrios Siadimas, Vasilios Busawon, Krishna Gao, Zhiwei Siano, Pierluigi Abbaszadeh, Masoud Unit of Industrial Automation Industrial Systems Institute Rion Patras26504 Greece Industrial Systems Institute RC Athena Rion Patras26504 Greece Department of Electrical and Computer Engineering University of Patras Rion Patras26504 Greece Nonlinear Control Group University of Northumbria NewcastleNE1 8ST United Kingdom Department of Industrial Engineering University of Salerno Fisciano84084 Italy GE Global Research General Elecric NiskayunaNY12309 United States

the problem of statistical fault diagnosis for the quadruple watertanks system is examined. the solution of the fault diagnosis problem for the dynamic model of the four-water tanks system is a non-trivial case, due to nonlinearities and the system's multivariable structure. In the article's approach, the system's dynamic model undergoes first approximate linearization around a temporary operating point which is recomputed at each sampling period. the linearization procedure relies on Taylor series expansion and on the computation of the Jacobian matrices of the state-space description of the system. the H-infinity Kalman Filter is used as a robust state estimator for the approximately linearized model of the quadruple water tanks system. By comparing the outputs of the H-infinity Kalman Filter against the outputs measured from the real water tanks system the residuals sequence is generated. It is concluded that the sum of the squares of the residuals' vectors, being weighted by the inverse of the associated covariance matrix, stands for a stochastic variable that follows the χ2 distribution. As a consequence, a statistical method for condition monitoring of the quadruple water tanks system is drawn, by using the properties of the χ2 distribution and the related confidence intervals. Actually, normal functioning can be ensured as long as the value of the aforementioned stochastic variable stays within the previously noted confidence intervals. On the other side, one can infer the malfunctioning of the quadruple water tanks system with a high level of certainty (e.g. of the order of 96% to 98%), when these confidence intervals are exceeded. the article's method allows also for fault isolation, that is for identifying the specific component of the quadruple water tanks system that has been subject to fault or cyber-attack. © the Authors, published by EDP Sciences, 2018.

关键词： Water tanks

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Developing a Smart IoT Solution to Monitor on-Bed Movement Patterns

Developing a Smart IoT Solution to Monitor on-Bed Movement P...

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international conference on Information Technology (INCIT)

作者： Prakrankiat Youngkong Worawit Panpanyatep Kitti thamrongaphichartkul Institute of Field Robotics King Mongkut's University of Technology Thonburi

ISBN: (数字)9781728166940

ISBN: (纸本)9781728193212

IoT devices and systems become a part of modern living. they are mostly used to monitor daily activities, especially related to personal health and fitness. In fact, it is getting more crucial during the COVID-19 pandemic. In this study, a smart monitoring and alarming IoT system called “NEF” was modified to recognize on-bed movement patterns including prone position applying different machine learning techniques. On-bed movement patterns were collected from 7 subjects. Considering only prone and supine positions, the models obtained from multilayer perceptron was the best. However, random forest yielded the highest overall correctly classified percentage. Further investigation is likely to include beddings such as pillows and blankets.

关键词： Radio frequency Monitoring COVID-19 Stress Signal processing Robots Hardware

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Rapid Power Compensation Based Flexible DC Transmission System Control Strategy for Supporting Frequency Stability of Islanded Grids

Rapid Power Compensation Based Flexible DC Transmission Syst...

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IEEE international conference on Power and Energy Applications (ICPEA)

作者： Jiangsheng Yu Xin Xiang Yuefa Guo Xi Zhang Dandan Wu Jianquan Shi Dongguan Power Supply Bureau Guangdong Power Grid Co. Ltd Dongguan China NR Electric Co. Ltd Nanjing China School of Automation Nanjing Institute of Technology Nanjing China

ISBN: (纸本)9781665487627

the large-scale islanded power grids decouples the frequency of public power system and causes function loss to clamp its frequency, threatening the stability of power systems. the flexible DC transmission system can transmit power to the islanded power grids and improves the frequency stability of islanded grids by adding frequency control, which can actively participate in the dynamic process of frequency quality improvement. However, the frequency instability of islanded grids is easy to occur, and the typical frequency controls (such as droop, inertia and PD control) cannot compensate the power deficiency quickly and sufficiently. Considering the limitation of conventional strategies, the rapid power compensation (RPC) based frequency control strategy was proposed in this paper, which quantifies the transmitted power between the inverter and the islanded grid to determine the maximum power that can be generated by the inverter. When the disturbance of the islanded grid exceeds the specified threshold, the maximum power is directly used to fully use the capacity of the inverter and fill the power gap of the islanded grid to the maximum extent, and hence reduce frequency deviation and frequency change rate quickly. Besides, the simulation results also show that the RPC control is more suitable for low inertia systems, because of its remarkable effect under large disturbances.

关键词： Time-frequency analysis Reactive power Simulation Rectifiers Power system stability Inverters Stability analysis

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Benchmarking a ROS 2-Based Indirect SLAM on Edge Devices

Benchmarking a ROS 2-Based Indirect SLAM on Edge Devices

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robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Valentino Behret Regina Kushtanova Frank Palme Department of Mechanical Automotive and Aeronautical Engineering Laboratory for 3D Measuring Systems and Computer Vision Munich University of Applied Sciences Munich Germany

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

this study provides insights into SLAM performance on embedded systems and introduces an unsupervised parameter tuning approach for enhanced localisation accuracy. Our paper benchmarks a ROS 2-based indirect Simultaneous Localisation and Mapping (SLAM) system across six NVIDIA Jetson devices: Orin Nano 4 GB, Orin Nano 8 GB, Orin NX 8 GB, Orin NX 16 GB, AGX Orin 32 GB Auvidea, and AGX Orin 32 GB Devkit, using sequences from the KITTI dataset. the edge devices differ significantly in GPU computing power, number of CPU cores, CPU clock frequency as well as memory. SLAM evaluations are conducted within Docker containers to ensure consistency, with feature detection parameters optimised using an unsupervised tuning approach for each device. In addition to localisation accuracy, hardware utilisation is analysed, revealing that less than a half of CPU capabilities and approximately 5– 10 % of GPU power are utilised. the results indicate that in the default configuration devices with lower computing power demonstrate higher fluctuation in SLAM localisation accuracy. However, optimising feature parameters improves accuracy stability, especially for less powerful edge devices, indicating that even lower-powered but more energy-saving devices can achieve similar performance when an optimised balance between feature quantity and runtime constraints is achieved.

关键词： Performance evaluation Accuracy Simultaneous localization and mapping Runtime Benchmark testing Nanoscale devices Reproducibility of results Standards Tuning Optimization

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Photovoltaic Power Generation Forecasting Based on TCN-Transformer Model

Photovoltaic Power Generation Forecasting Based on TCN-Trans...

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Artificial Intelligence and Electromechanical automation (AIEA), international conference on

作者： Linhan Wu Jizhou Yu Yuxin Dai Tianlu Gao Jun Zhang School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

this paper proposes a TCN-Transformer hybrid model based on the Temporal Convolutional Network (TCN) and the Transformer model to enhance the accuracy of photovoltaic (PV) power forecasting. Given the volatility and randomness of photovoltaic power generation, accurate power prediction is crucial for the scheduling and stability of the power system. the model combines TCN’s sensitivity in capturing local patterns and long-distance dependencies with the Transformer’s ability to process sequences in parallel through its self-attention mechanism. through a case study, the model is validated to be more effective in handling time series data and large-scale datasets, and it demonstrates high accuracy and generalization capabilities in the task of photovoltaic power forecasting. Firstly, the paper introduces the correlation analysis between weather factors and photovoltaic forecasting, along with the evaluation metrics for prediction. Following this, it provides a detailed description of the proposed hybrid model, including the integration of the TCN and the Transformer, and their roles in photovoltaic power forecasting. then, a practical case study is conducted to test and analyze the performance of the hybrid model, demonstrating its superior capabilities. Finally, the paper concludes with a summary and future outlook.

关键词： Photovoltaic systems Adaptation models Accuracy Computational modeling Predictive models Transformers Hybrid power systems Data models Convolutional neural networks Forecasting

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Deep Reinforcement Learning for Combined Coverage and Resource Allocation in UAV-Aided RAN-Slicing

Deep Reinforcement Learning for Combined Coverage and Resour...

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international conference on Distributed Computing in Sensor systems (DCOSS)

作者： Lorenzo Bellone Boris Galkin Emiliano Traversi Enrico Natalizio Autonomous Robotics Research Center - Technology Innovation Institute UAE Wireless Communications Group - Tyndall National Institute Ireland LIPN UMR CNRS 7030 Université Sorbonne Paris Nord France LORIA UMR CNRS 7503 Université de Lorraine Nancy France

Network slicing is a well assessed approach enabling virtualization of the mobile core and radio access network (RAN) in the emerging 5th Generation New Radio. Slicing is of paramount importance when dealing with the emerging and diverse vertical applications entailing heterogeneous sets of requirements. 5G is also envisioning Unmanned Aerial Vehicles (UAVs) to be a key element in the cellular network standard, aiming at their use as aerial base stations and exploiting their flexible and quick deployment to enhance the wireless network performance. this work presents a UAV-assisted 5G network, where the aerial base stations (UAV-BS) are empowered with network slicing capabilities aiming at optimizing the Service Level Agreement (SLA) satisfaction ratio of a set of users. the users belong to three heterogeneous categories of 5G service type, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), and massive machine-type communication (mMTC). A first application of multi-agent and multi-decision deep reinforcement learning for UAV-BS in a network slicing context is introduced, aiming at the optimization of the SLA satisfaction ratio of users through the joint allocation of radio resources to slices and refinement of the UAV-BSs 2-dimensional trajectories. the performance of the presented strategy have been tested and compared to benchmark heuristics, highlighting a higher percentage of satisfied users (at least 10.5% more) in a variety of scenarios.

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Enhancing engineering education by means of the promotion of entrepreneurial mindsets and attitudes for societal challenges

Enhancing engineering education by means of the promotion of...

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international conference of the Portuguese Society for Engineering Education (CISPEE)

作者： S. Tavares B. C. Gabriel R. Valente J. Oliveira C. Relvas P. Prates R. Sousa V. Neto C. Carlos C. Figueiredo Department of Mechanical Engineering (DEM) Centre for Mechanical Technology and Automation (TEMA) Intelligent Systems Associate Laboratory (LASI) University of Aveiro Portugal

the development of skills and awareness of entrepreneurship and innovation topics in engineering curricula has been growing by diverse measures, such as by means of team-working sessions towards real-world problems, promotion of problem-solving assignments, and external initiatives to exploit ideas and to promote the development of new products or services. this paper addresses an approach taken as a complementary, extracurricular, education program together with a Product Development Project course, activities promoted by a joint initiative of several European universities in the form of the “Start for Future” (SFF) program. this initiative allowed students to explore the innovation and entrepreneurship dimensions of their ongoing projects with tandem teams from other institutions and external experts. the potential impact of this integrated, international, program is reviewed, considering both the work developed by students as well as analyzing the competences acquired during the extra-curricular activities. these initiatives proved to attain a positive effect on students and the learning process, stimulating entrepreneurial mindsets and attitudes, as well as complementing the training of the student on a number of transferable competences that are crucial for future engineers.

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