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共 35064 条记录，以下是331-340 订阅

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Predictive Modeling of Energy Consumption for Building automation systems Using Deep Learning 3

Predictive Modeling of Energy Consumption for Building Autom...

引用

3rd ieee international conference on intelligent Techniques in control, Optimization and Signal Processing, INCOS 2024

作者： Sivasankari, N. Rathika, P. Psn College of Engineering and Technology Department of Electrical and Electronics Engineering Tirunelveli India Psn College of Engineering and Technology Department of Electronics and Communication Engineering Tirunelveli India

ISBN: (纸本)9798350361186

In the realm of building automation systems, efficient energy consumption modeling stands as a crucial element for sustainable and intelligent environments. This paper presents a predictive modeling approach utilizing deep learning networks like Long Short-Term Memory (LSTM) neural networks, alongside comparisons with Gated Recurrent Unit (GRU) and Bidirectional LSTM (Bi-LSTM) architectures, for predicting energy utilization within buildings. The study employs a smart home dataset from the UMASS Repository, demonstrating the model's effectiveness in capturing temporal dependencies and delivering accurate predictions. The methodology encompasses comprehensive data preprocessing, model training, and evaluation using key performance metrics. Significantly, the obtained results showcase the superior performance of the LSTM model over GRU and Bi-LSTM, with a Mean Absolute Error (MAE) of 0.2662, Root Mean Squared Error (RMSE) of 0.4067, and Mean Squared Error (MSE) of 0.1654. These metrics underscore the model's capability to provide reliable and accurate predictions, thereby contributing to optimizing energy management within building automation systems. The demonstrated success of the predictive model highlights its potential significance in advancing sustainable practices, promoting resource efficiency, and facilitating intelligent decision-making within the realm of intelligent buildings. © 2024 ieee.

关键词： Long short-term memory

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Positioning cyber-Physical systems and Digital Twins in Industry 4.0 7

Positioning Cyber-Physical Systems and Digital Twins in Indu...

引用

ieee 7th international conference on Industrial cyber-Physical systems (ICPS)

作者： Pires, Flavia Melo, Victoria Queiroz, Jonas Moreira, Antonio Paulo de la Prieta, Fernando Estevez, Elisabet Leitao, Paulo Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI Campus Santa Apolonia P-5300253 Braganca Portugal Sao Paulo State Univ UNESP IGCE DEMAC BR-13506900 Rio Claro SP Brazil Univ Porto Fac Engn INESC TEC INESC Technol & Sci Rua Dr Roberto Frias P-4200465 Porto Portugal Univ Salamanca BISIIE Digital Innovat Hub Edificio Multiusos I D I Salamanca 37007 Spain Univ Jaen Elect & Automat Engn Dept Jaen Spain Inst Politecn Braganca Lab Associado Sustentabilidade & Tecnol Regioes M Campus Santa Apolonia P-5300253 Braganca Portugal

ISBN: (纸本)9798350363029;9798350363012

Industry 4.0 has brought innovative concepts and technologies that have greatly improved the development of more intelligent, flexible and reconfigurable systems. Two of these concepts, cyber-Physical systems (CPSs) and Digital Twins (DTs), have gained significant attention from various stakeholders, e.g., researchers, industry practitioners, and governmental organizations. Both are vital to support the digitalisation of products, machines, and systems, and they focus on the integration of physical and cyber processes, where one affects the other through feedback loops. Having this in mind, this paper aims to better understand how CPS and DT are correlated, particularly exploring their similarities and differences, their positioning within the Industry 4.0 paradigm, and their convergence to develop Industry 4.0 solutions. Some research challenges to develop Industry 4.0 solutions by integrating these concepts are also discussed.

关键词： cyber-Physical systems Digital Twin RAMI4.0

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intelligent Vehicle Trajectory Tracking control Based on H∞ Proportional-differential controller 6

Intelligent Vehicle Trajectory Tracking Control Based on H∞...

引用

ieee 6th international conference on Industrial cyber-Physical systems (ICPS)

作者： Pan, Gongwei Feng, Zhiyong Guo, Huiru Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan Peoples R China

ISBN: (纸本)9798350311259

In order to improve the trajectory tracking accuracy and stability of intelligent vehicles, this paper proposes a vehicle trajectory tracking control method based on H8 proportional-differential (PD) control. Taking the two-degreeof-freedom vehicle model considering lateral motion and yaw motion as the research object, we establish the state space model based on tracking error. Then, the PD control problem of the model is transformed into a static output feedback (SOF) control problem, and the coordinate transformation matrix (CTM) method is used to solve the problem by multiple iterative optimizations. Finally, the H8PD controller satisfying pole configuration constraints and H8 performance constraints is obtained. The co-simulation of MATLAB/Simulink and Carsim shows that the controller has high tracking accuracy based on ensuring vehicle stability in both the double lane-change condition and the serpentine condition.

关键词： trajectory tracking H8 PD control coordinate transformation matrix

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Smart Object Detection using ESP32-CAM based on YOLO Algorithm 2

Smart Object Detection using ESP32-CAM based on YOLO Algorit...

引用

2nd international conference on intelligent cyber Physical systems and Internet of Things (ICoICI)

作者： Narwaria, Ravindra Pratap Ahirwar, Anand Prajapati, Abhinay K. Kumar, Abhishek Tiwari, Arin K. MITS Dept Elect Engn Gwalior MP India

ISBN: (纸本)9798331540661;9798331540678

In the present research work, a system is developed that can detect objects in real-time using a combination of the ESP32 CAM module and Python programming. The goal was to show how affordable hardware and free software can be used to make a system that recognizes objects quickly and accurately. By using computer vision and machine learning tricks, the proposed system can figure out the different objects with great precision. The setup process involves putting some code onto the ESP32 CAM module, finding its IP address, and then making it work smoothly with Python. The proposed system was tested in different situations, like watching for things in surveillance, making tasks easier with automation, and helping out in assistive technologies.

关键词： ESP32-CAM Module Computer Vision Real-time Object Detection Machine Learning (ML) Surveillance systems Object Recognition Python Programming Image Processing YOLO Open CV

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A control and Attack Detection Scheme for Fuzzy systems against cyber-attacks

A Control and Attack Detection Scheme for Fuzzy Systems agai...

引用

ieee international conference on Fuzzy systems (FUZZ-ieee)

作者： Zhang, Haili Li, Linlin Qiao, Liang Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Shunde Grad Sch Univ Sci & Technol Beijing Foshan 528399 Peoples R China

ISBN: (纸本)9798350332285

This paper studies the detection of cyber-attacks on fuzzy systems in cyber physical systems under the unified framework of control and detection. To this end, the fuzzy systems under cyber physical systems and the different types of spoofing attacks are first introduced. Then, a control and attack detection scheme for fuzzy systems is presented. The essential idea behind the proposed approach lies in detecting the cyber-attacks structurally by expanding the residual space using observer-based residual signals and control-based residual signals. In addition, a detection scheme based on encrypted transmissions of control and monitoring signals in the feedback control system is proposed, which can effectively prevent attackers from stealing system information and achieve the detection of cyber-attacks.

关键词： Fuzzy systems cyber physical systems the control and detection framework residual generator feedback control systems

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Testing Scenario Framework for intelligent Vehicle cyber-Physics System 24

Testing Scenario Framework for Intelligent Vehicle Cyber-Phy...

引用

24th COTA international conference of Transportation Professionals: Resilient, intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Gu, Zhenyu Liu, Rentao Li, Dongyang Jiang, Wei School of Automation Chongqing Univ. Chongqing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

Scenario-based testing holds significant importance in the intelligent vehicle ecosystem, with the framework of the scenario being a fundamental consideration in its construction. intelligent vehicles are typical complex cyber-physical systems that deeply integrate automotive, transportation, and information communication systems. Therefore, it is necessary to analyze and deconstruct the framework of the scenario from the perspective of CPS. Combining scenario construction with the RFLP (Require-Function-Logic-Physics) framework design method, we propose an RFLCP (Require-Function-Logic-cyber-Physics) framework for testing the scenario of IVCPS (intelligent vehicle cyber-physics systems). This framework achieves layer-by-layer decoupling of IVCPS in the order of scenario requirements, functional scenarios, logical scenarios, and cyber-physics scenarios, and based on typical scenarios, implement each level of the framework in Magic Draw. The research results can guide the generation and construction of intelligent vehicle testing scenarios. © ASCE.

关键词： Data communication systems

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Event-Driven control of Multi-Agent systems Based on Discrete Communication 2

Event-Driven Control of Multi-Agent Systems Based on Discret...

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2nd international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2024

作者： Yu, Wenduo Suo, Pengxiang Guo, Zongjin Zhang, Xiaolong Fei, Jianing Deng, Linjiang Yingkou Power Supply Company State Grid Liaoning Electric Power Co. Ltd. Yingkou China

ISBN: (纸本)9798350373318

A new control strategy for tracking multiple agents is proposed, utilizing discrete communication methods. This strategy incorporates adaptive techniques to minimize reliance on global information and implements event-driven mechanisms for discrete measurements between neighboring agent. Simulation results confirm the effectiveness of this strategy in regulating load voltage. © 2024 ieee.

关键词： Multi agent systems

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SOC Estimation of Lithium-ion Battery Based on Dual Time Scale SVD-UKF Algorithm 7

SOC Estimation of Lithium-ion Battery Based on Dual Time Sca...

引用

ieee 7th international conference on Industrial cyber-Physical systems (ICPS)

作者： Ye, Zhenhan Ye, Zehua Zhang, Dan Ge, Qiyun Zhejiang Univ Technol Coll Informat Engn Hangzhou Peoples R China Kerun Intelligent Control Co Quzhou Peoples R China

ISBN: (纸本)9798350363029;9798350363012

To solve the inconsistency problem in the charge-discharge process in battery packs from the energy storage system, this paper introduces one method to estimate the battery state of charge (SOC) based on the dual time-scale singular value decomposition-unscented Kalman filter (SVD-UKF). First, a second-order resistor-capacitor (RC) equivalent circuit model (ECM) is developed. The model parameters are recognized by utilizing the forgetting factor recursive least square (FFRLS) method. Second, a dual time-scale UKF algorithm is adopted to decrease the system's computational complexity and improve the estimation reliability. It tracks the SOC of the cells with the largest and smallest capacity on a micro time scale and the SOC of the remaining cells on a macro time scale. Moreover, the stability of the algorithm is ensured by singular value decomposition. Finally, a simulation study is done to demonstrate this algorithm's effectiveness.

关键词： Lithium-ion battery Dual time scale UKF SOC estimation

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Missing-Pattern-Aware-Based Multi-Model Imputation Method for Wastewater Treatment Process 13

Missing-Pattern-Aware-Based Multi-Model Imputation Method fo...

引用

13th ieee international conference on cyber technology in automation, control, and intelligent systems, cyber 2023

作者： Sun, Meiting Han, Honggui Li, Fangyu Beijing University of Technology Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350315196

In wastewater treatment process (WWTP), data-based implement techniques ensure the stable operation and reduce energy consumption. Different missing patterns of missing values often occur due to some harsh environments and sensor failures. However, existing imputation methods are difficult to obtain satisfactory data for implementation techniques as they only consider a single missing pattern. To solve this problem, a missing-pattern-aware-based multi-model imputation method (MPAMI) is proposed. First, a missing pattern aware network combining the advantages of the encoder and the axial attention mechanism is designed to identify different missing patterns. The network employs the encoder to extract nonlinear feature representations and utilizes the axial attention mechanism to focus on the most informative differential features. Second, a hybrid multi-model imputation method based on the long short-term memory network and the denoising autoencoder is developed to recover missing values. The imputation method utilizes the spatiotemporal information of missing patterns to improve imputation performance. Finally, experiments are conducted on a real WWTP dataset to validate the imputation performance of the proposed MPAMI. © 2023 ieee.

关键词： Energy utilization

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A Physiological Signal Emotion Recognition Method Based on Domain Adaptation and Incremental Learning 1

A Physiological Signal Emotion Recognition Method Based on D...

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1st international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2022

作者： Li, Junnan Wang, Xiaoping Huazhong University of Science and Technology The School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781665452151

Temporal concept shift (TCS) is an unavoidable problem in physiological signal-based emotion recognition tasks, i.e., the data distribution of physiological signals is constantly changing over time, which gradually degrades the model accuracy. To this end, we propose a method based on a combination of domain adaptation and incremental learning to reduce the impact of temporal concept drift. In this paper, domain adaptation is used to reduce the distribution differences and incremental learning is used to prevent the learned knowledge from being forgotten. Finally, we validate the effectiveness of our approach on two real datasets. © 2023 ieee.

关键词： Emotion Recognition

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