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Analysis of HVAC sensor characteristics for operation and maintenance of the indoor environment: A case research on public building HVAC

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Building Simulation 2025年 1-24页

作者： Zhang, Boyan Wang, Jiaming Shangguan, Liuyang Rezgui, Yacine Ghoroghi, Ali Cao, Ximing Song, Chengzhe Ding, Menglin Zhao, Tianyi Institute of Building Energy Department of Civil Engineering Dalian University of Technology Dalian China School of Engineering Cardiff University Cardiff United Kingdom School of instrument and electronics North University of China Taiyuan China School of Information Science and Technology Fudan University Shanghai China Landscape Architecture Rhode Island School of Design Providence02903 United States Dalian Shenghe Automatic Control Technology Co. Ltd Dalian China

Sensors are a crucial component in heating, ventilation, and air conditioning (HVAC) control systems, and the quality of them plays an important role in control accuracy. In the research of fault detection and control optimization, improving sensor data quality has inspiring potential in application. It has been largely limited to the application of signal processing methods in research focus, whereas a detailed analysis of the characteristics of signals from various sensors of the HVAC system has not been conducted. Therefore, this study analyzes the time-frequency domain characteristics of control sensors within HVAC systems through integrating the structural design and control logic of such systems. Additionally, the research examines the correlations between control sensors in HVAC systems. Based on statistical principles and the energy-mass dynamic laws of the equipment, this paper defines first-class (I) correlated sensors and second-class (II) correlated sensors. To sum up, the main contribution of this paper is conducting a fundamental study on the characteristics of control sensors within HVAC systems, providing theoretical reference for future research on HVAC system fault diagnosis and control optimization. © Tsinghua University Press 2025.

关键词： HVAC

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Retinal disorder diagnosis based on hybrid deep learning models

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Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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UAV-Assisted IRS System in 5 G and Beyond: Improving Reliability and Enhancing the Network Life Span

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IEEE Transactions on Mobile Computing 2025年

作者： Kumar, Pankaj Goel, Nikita Tolani, Manoj Manipal Institute of Technology Department of Information and Communication Technology Manipal576104 India Manipal Institute of Technology Department of Instrumentation and Control Engineering Manipal576104 India

This paper proposes an unmanned aerial vehicle (UAV)-assisted intelligent reflecting surface (IRS) for device-to-device (D2D) communication in infrastructure-less scenarios. The aim of this paper is to enhance the reliability among D2D ground users (GUs) and extend the lifespan of 5 G and beyond 5 G (B5G) wireless communication system. This work may be applicable for packet delivery in bustling urban areas, especially where ground-to-ground (G2G) links are in deep fade. For modeling air-to-ground (A2G) links among GUs to IRS/UAV and IRS/UAV to GUs, we consider a height-dependent Nakagami-m channel model for small-scale fading and height-dependent path-loss exponent for modeling large-scale fading. The lifespan of the network is improved by proposing height-dependent energy harvesting (EH) at UAV. We derive the cumulative distribution function (CDF) of the signal-to-noise ratio (SNR) whenever the signal reaches the receiving node, either via UAV or via IRS. We also develop the expression of spectral efficiency and derive a closed-form expression of an outage probability by taking the combined effect of the signal for the proposed scenario using decode-and-forward (DF) and amplify-and-forward (AF) relaying at the UAV. Additionally, the statistical parameters such as mean, variance, and probability density function (PDF) of total noise are derived, which is useful at the receiver node for estimating the bit error rate (BER). The analytical result is validated with simulation results, and the work is compared with the existing state-of-the-art. © 2002-2012 IEEE.

关键词： Distribution functions

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Dynamic Regret for Distributed Online Composite Optimization

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IEEE Transactions on Automatic control 2025年第5期70卷 3056-3071页

作者： Hou, Ruijie Yu, Yang Li, Xiuxian Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai201800 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai Institute of Intelligent Science and Technology Shanghai201210 China

This article focuses on online composite optimization over multiagent networks. In the distributed setting, each agent has its own local loss function, which consists of a convex, strongly convex or strongly convex and smooth function, and a time-varying nonsmooth regularizer. Two distributed online algorithms are proposed and corresponding dynamic regrets are analyzed. Two proposed algorithms are based on signs of relative states. The first algorithm obtains (Formula presented) dynamic regret bound when each local loss is a general convex composite function, where CT is the path variation. If CT can be estimated in advance for convex or strongly convex local loss with a time-varying nonsmooth regularizer, then dynamic regret bounds are, respectively, in the order of (Formula presented) and o (log T(1 + CT)). The second algorithm is based on the first one, especially for handling the local loss composed of a strongly convex and smooth function with a nonsmooth regularizer, and then obtains o (1 + CT) dynamic regret bound. In the end, numerical results are given to support the theoretical findings. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Advances in invasive and non-invasive glucose monitoring: A review of microwave-based sensors

Sensors and Actuators Reports

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Sensors and Actuators Reports 2025年 9卷

作者： Alsultani, Ameer B. Kovács, Katalin Chase, J. Geoffrey Benyo, Balazs Department of Control Engineering and information Technology Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Budapest Hungary Department of Informatics Széchenyi István University Győr Hungary Department of Mechanical Engineering University of Canterbury Christchurch New Zealand Department of Communications Engineering University of Technology Iraq

Effective and continuous glucose monitoring is critical in managing diabetes, which remains a global health challenge affecting millions. Traditional invasive glucose monitoring methods, although accurate, cause discomfort and are unsuitable for frequent measurements necessary for optimal diabetes management. To overcome these limitations, microwave-based sensors have emerged as promising alternatives, providing both invasive and non-invasive monitoring capabilities. This review critically evaluates recent advancements in microwave-based glucose sensors, emphasizing their design methodologies, sensitivity, accuracy, and clinical applicability. By leveraging unique dielectric properties of blood and tissues affected by glucose concentrations, microwave sensors enable precise and potentially pain-free glucose measurements. Despite significant progress, existing sensor technologies face challenges including limited sensitivity ranges, interference from biological tissues, and practical considerations for clinical adoption. This paper aims to guide researchers and healthcare providers by highlighting recent technological innovations, addressing current limitations, and suggesting directions for future research to advance glucose monitoring technologies towards widespread clinical use. © 2025

关键词： Noninvasive medical procedures

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Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling Under Data Governance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 351-361页

作者： Qin, Zhaoming Dong, Nanqing Liu, Di Wang, Zhefan Cao, Junwei EPFL Automatic Control Laboratory Lausanne1015 Switzerland Shanghai Artificial Intelligence Laboratory Shanghai200232 China Tsinghua University Department of Electrical Engineering Beijing100084 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

As a data-driven approach, multi-agent reinforcement learning (MARL) has made remarkable advances in solving cooperative residential load scheduling problems. However, centralized training, the most common paradigm for MARL, limits large-scale deployment in communication-constrained cloud-edge environments. As a remedy, distributed training shows unparalleled advantages in real-world applications but still faces challenge with system scalability, e.g., the high cost of communication overhead during coordinating individual agents, and needs to comply with data governance in terms of privacy. In this work, we propose a novel MARL solution to address these two practical issues. Our proposed approach is based on actor-critic methods, where the global critic is a learned function of individual critics computed solely based on local observations of households. This scheme preserves household privacy completely and significantly reduces communication cost. Simulation experiments demonstrate that the proposed framework achieves comparable performance to the state-of-the-art actor-critic framework without data governance and communication constraints. © 2023 IEEE.

关键词： Reinforcement learning

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Mixtures of ensembles: System separation and identification via optimal transport

arXiv

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arXiv 2025年

作者： Elvander, Filip Haasler, Isabel Department of Information and Communications Engineering Aalto University Finland Division of Systems and Control Department of Information Technology Uppsala University Sweden

Crowd dynamics and many large biological systems can be described as populations of agents or particles, which can only be observed on aggregate population level. Identifying the dynamics of agents is crucial for understanding these large systems. However, the population of agents is typically not homogeneous, and thus the aggregate observations consist of the superposition of multiple ensembles each governed by individual dynamics. In this work, we propose an optimal transport framework to jointly separate the population into several ensembles and identify each ensemble’s dynamical system, based on aggregate observations of the population. We propose a bi-convex optimization problem, which we solve using a block coordinate descent with convergence guarantees. In numerical experiments, we demonstrate that the proposed approach exhibits close-to-oracle performance also in noisy settings, yielding accurate estimates of both the ensembles and the parameters governing their dynamics. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Distributed Estimation and Motion control in Multi-Agent Systems Under Multiple Attacks

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IEEE Transactions on Automation Science and engineering 2025年 22卷 12548-12559页

作者： Jenabzadeh, Ahmadreza Shu, Zhan Huang, Tingwen Zhu, Quanmin Shang, Yilun Cui, Yukang Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Peng Cheng Laboratory Shenzhen518000 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China University of the West of England School of Engineering BristolBS16 1QY United Kingdom Northumbria University Faculty of Engineering and Environment Department of Computer and Information Sciences Newcastle upon TyneNE1 8ST United Kingdom

This paper addresses the problem of distributed estimation and motion control (DEMC) in multi-agent systems (MASs) with both linear and Lipschitz nonlinear dynamics. Unlike conventional DEMC methods designed for MASs under ideal conditions, this work investigates scenarios where all agents are vulnerable to various forms of attacks. The considered attacks comprise false-data injection (FDI) attacks and denial of service (DoS) attacks that affect the communication channels among agents to destabilize the MAS. Also, the unbounded actuator attacks which exist in practical environments to intentionally degrade the MAS performance is considered. To cope with these kinds of attacks, two novel resilient approaches are established aimed at estimating and following a mobile target under attacks. The proposed distributed attack-resilient control strategies are designed based on a dual-layer structure, guaranteeing effective DEMC with an ultimately bounded error. The results from two simulation examples are provided to validate the presented algorithms. © 2004-2012 IEEE.

关键词： Multi agent systems

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Distributed Adaptive Tracking control for Fuzzy Nonlinear MASs Under Round-Robin Protocol

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IEEE Transactions on Fuzzy Systems 2025年第5期33卷 1488-1498页

作者： Fan, Sha Meng, Min Fu, Yukai Deng, Chao Nanjing University of Posts and Telecommunications College of Automation College of Artificial Intelligence Nanjing210023 China Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai200070 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing210049 China

In this article, the cooperative fuzzy tracking control problem for a type of high-order nonlinear multi-agent systems under the Round-Robin (RR) communication protocol is solved. To effectively reduce the communication among agents, an RR communication protocol is first proposed, where each agent can communicate with only one neighbor at any given time. Based on the developed communication protocol, a hierarchical control approach is introduced, consisting of a distributed observer layer that utilizes information from both local and neighboring agents, and a decentralized control layer that operates solely based on local agent information. Specifically, a distributed observer is designed in the distributed observer layer to achieve the distributed observation objective by introducing a time-varying gain in the observer input. Furthermore, an improved distributed observer with the upper triangular form is constructed to produce a signal with high-order derivatives. In the decentralized control layer, fuzzy adaptive controllers are designed for all agents by using the backstepping technique. By using the Lyapunov stability theory, rigorous stability analysis shows that the cooperative fuzzy tracking control problem is solved under the developed hierarchical control approach. In the end, a simulation example is presented to demonstrate the validity of our proposed method. © 1993-2012 IEEE.

关键词： Protocols Observers Stability analysis Decentralized control Backstepping Vectors Symmetric matrices Network topology Telecommunications System dynamics

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