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Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3235-3248页

作者： Liang, Weisheng Amer, Abdelhakim Mehndiratta, Mohit Chen, Zheng Yao, Bin Kayacan, Erdal Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China Aarhus University Artificial Intelligence in Robotics Laboratory Department of Electrical and Computer Engineering Aarhus8000 Denmark GIM Robotics Espoo02650 Finland Zhejiang University Ocean College Ocean Research Center of Zhoushan Zhoushan316021 China Purdue University School of Mechanical Engineering West Lafayette47907 United States Department of Electrical Engineering and Information Technology Paderborn33098 Germany

With increasingly challenging applications for quadrotors, higher requirements are emerging for tracking accuracy and safety. While high accuracy is a prerequisite for complex tasks, safety is ensured through tolerance to actuator faults and resistance to external disturbances. In this article, adaptive robust control (ARC) integrated with Gaussian processes (GPs), i.e., ARC-GP, is proposed to achieve enhanced accuracy, fault tolerance, and anti-disturbance. These three requirements are interrelated and affected by uncertainties. The primary idea of this article is to categorize uncertainties into parametric and nonparametric types, which are then addressed through parameter adaptation and GP, respectively. First, a detailed dynamic model is established, including actuator models that reflect different types of faults corresponding to changes in different physical parameters. Then, parameter adaptation is designed, with direct and indirect methods adopted for different parameters. In particular, the actuator parameters are effectively estimated to achieve targeted fault compensation. Regarding GP for nonparametric uncertainties, its model parameters are also updated via parameter adaptation. The GP thereby also learns parameter estimation errors along with external disturbances. Accordingly, ARC controllers are designed, for which robust feedback terms are constructed to further mitigate uncertainties on the basis of the covariances predicted by GP. The experiments demonstrate that the proposed ARC-GP can actively tolerate various types of actuator faults and better resist wind disturbances. © 2013 IEEE.

关键词： Robust control

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Real-Time Circuit Optimizations for Dual-Function Radar-Communications

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 101-111页

作者： Haug, Samuel Goad, Adam Egbert, Austin Baylis, Charles Martone, Anthony Marks, Robert J. Baylor University WacoTX76798 United States Baylor University Department of Electrical and Computer Engineering WacoTX76798 United States Adelphi Laboratory Center Army Research Laboratory AdelphiMD20783 United States

Spectral efficiency has become increasingly important in the modern congested spectral environment. Directional modulation multiplexing helps by using spatial diversity to transmit different messages in different directions at the same frequency. This approach can be used to provide dual-function radar-communication transmissions that are direction-specific. In these transmissions, the vector current excitations of different array elements are calculated to provide the directional transmission, resulting in different output power levels for the different elements. This approach results in varying levels of compression for the element amplifiers, leading to varying distortion and performance. Mutual coupling between elements can change the antenna reflection coefficients, resulting in distortion of the directionally transmitted symbols and further alter element performance. Real-time reconfigurable matching circuitry, placed between each element amplifier device and antenna, ensures that each amplifier is optimized to maximize gain while minimizing distortion when the frequency, intended directions, or directional transmission symbol combinations are changed. An algorithm is proposed and demonstrated in simulation which uses high-speed plasma-switched impedance tuners, in-situ RF current measurements, and amplifier pre-characterization to quickly optimize array circuitry. These optimizations may be completed in microseconds, allowing reconfigurability commensurate with pulse-to-pulse adaptivity relative to the radar function of the transmission. © 2023 IEEE.

关键词： Real time systems

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Multi-Scale Fusion and Decomposition Network for Single Image Deraining

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IEEE Transactions on Image Processing 2024年 33卷 191-204页

作者： Wang, Qiong Jiang, Kui Wang, Zheng Ren, Wenqi Zhang, Jianhui Lin, Chia-Wen Wuhan University National Engineering Research Center for Multimedia Software School of Computer Science Wuhan430072 China Sun Yat-sen University School of Cyber Science and Technology Guangzhou510275 China Hangzhou Dianzi University College of Computer Science and Technology Hangzhou310018 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan

Convolutional neural networks (CNNs) and self-attention (SA) have demonstrated remarkable success in low-level vision tasks, such as image super-resolution, deraining, and dehazing. The former excels in acquiring local connections with translation equivariance, while the latter is better at capturing long-range dependencies. However, both CNNs and Transformers suffer from individual limitations, such as limited receptive field and weak diversity representation of CNNs during low efficiency and weak local relation learning of SA. To this end, we propose a multi-scale fusion and decomposition network (MFDNet) for rain perturbation removal, which unifies the merits of these two architectures while maintaining both effectiveness and efficiency. To achieve the decomposition and association of rain and rain-free features, we introduce an asymmetrical scheme designed as a dual-path mutual representation network that enables iterative refinement. Additionally, we incorporate high-efficiency convolutions throughout the network and use resolution rescaling to balance computational complexity with performance. Comprehensive evaluations show that the proposed approach outperforms most of the latest SOTA deraining methods and is versatile and robust in various image restoration tasks, including underwater image enhancement, image dehazing, and low-light image enhancement. The source codes and pretrained models are available at https://***/qwangg/MFDNet. © 1992-2012 IEEE.

关键词： Image reconstruction

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Optimizing Bearing Fault Detection:CNN-LSTM with Attentive TabNet for Electric Motor Systems

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computer Modeling in engineering & Sciences 2024年第12期141卷 2399-2420页

作者： Alaa U.Khawaja Ahmad Shaf Faisal Al Thobiani Tariq Ali Muhammad Irfan Aqib Rehman Pirzada Unza Shahkeel Nautical Science Department Faculty of MaritimeKing Abdulaziz UniversityJeddah22230Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Marine Engineering Department Faculty of MaritimeKing Abdulaziz UniversityJeddah22230Saudi Arabia Artificial Intelligence and Sensing Technologies(AIST)Research Center University of TabukTabuk71491Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia

Electric motor-driven systems are core components across industries,yet they’re susceptible to bearing *** fault diagnosis poses safety risks and economic instability,necessitating an automated *** study proposes FTCNNLSTM(Fine-Tuned TabNet Convolutional Neural Network Long Short-Term Memory),an algorithm combining Convolutional Neural Networks,Long Short-Term Memory Networks,and Attentive Interpretable Tabular *** model preprocesses the CWRU(Case Western Reserve University)bearing dataset using segmentation,normalization,feature scaling,and label *** architecture comprises multiple 1D Convolutional layers,batch normalization,max-pooling,and LSTM blocks with dropout,followed by batch normalization,dense layers,and appropriate activation and loss ***-tuning techniques prevent *** were conducted on 10 fault classes from the CWRU *** was benchmarked against four approaches:CNN,LSTM,CNN-LSTM with random forest,and CNN-LSTM with gradient boosting,all using 460 *** FTCNNLSTM model,augmented with TabNet,achieved 96%accuracy,outperforming other *** establishes it as a reliable and effective approach for automating bearing fault detection in electric motor-driven systems.

关键词： Electric motor-driven systems bearing faults automation fine tunned convolutional neural network long short-term memory fault detection

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QoS Prediction Model of Cloud Services Based on Deep Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 564-566页

作者： WenJun Huang PeiYun Zhang YuTong Chen MengChu Zhou Yusuf Al-Turki Abdullah Abusorrah Nanjing University of Information Science&Technology School of Computer and SoftwareNanjingChina IEEE New Jersey Institute of Technology Helen and John C.Hartmann Department of Electrical and Computer EngineeringNewarkUSA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Dear editor,This letter presents a deep learning-based prediction model for the quality-of-service(QoS)of cloud ***,to improve the QoS prediction accuracy of cloud services,a new QoS prediction model is proposed,which is based on multi-staged multi-metric feature fusion with individual *** multi-metric features include global,local,and individual *** results show that the proposed model can provide more accurate QoS prediction results of cloud services than several state-of-the-art methods.

关键词： services Services individual

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Smart Home Connectivity: Identifying the Best IoT Application Layer Protocols 14

Smart Home Connectivity: Identifying the Best IoT Applicatio...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Shahinzadeh, Hossein Azani, Zohreh Al-Hameedawi, Sundus F. Mohammadali Zanjani, S. Mehrabani-Najafabadi, Saiedeh Hemmati, Mohammadreza Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Department of Electrical Engineering University of Shahrekord Shahrekord Iran Smart Microgrid Research Center Najafabad Branch Islamic Azad University Najafabad Iran Faculty of Computer Engineering Najafabad Branch Islamic Azad University Najafabad Iran

ISBN: (纸本)9798331511272

The Internet of Things (IoT) bridges the physical and digital worlds by utilizing sensors, actuators, communication technologies, computing power, and data analytics to enable precise monitoring and control of the surrounding environment. Leveraging the data derived from IoT can lead to optimal decision-making for system management. In smart homes, IoT has ushered in a new generation known as connected homes. Given the diverse range of protocols available for the IoT application layer, selecting the appropriate protocol to connect smart home devices (based on their specific requirements) to the internet gateway is a critical issue. This paper first identifies the key factors influencing the choice of application layer protocols in smart homes. Then, it examines and analyzes some of the most commonly used IoT application layer protocols, including HTTP, MQTT, CoAP, WebSocket, DDS, XMPP, AMQP, STOMP, LwM2M, Zigbee, Z-Wave, BLE, and 6LoWPAN, based on these factors. Finally, recommendations for protocol selection in various sections of a smart home are provided based on the analysis conducted. ©2024 IEEE.

关键词： Smart homes

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electrically Tunable Microstrip U-Slot Antenna Using Ferroelectric BST Thin Film

Electrically Tunable Microstrip U-Slot Antenna Using Ferroel...

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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Alhassoon, Khaled Malallah, Yaaqoub Daryoush, Afshin S. Qassim University College of Engineering Department of Electrical Engineering Unaizah56452 Saudi Arabia Kuwait Institute of Scientific Research Energy and Building Research Center Shuwaikh70030 Kuwait Drexel University Department of Electrical and Computer Engineering PhiladelphiaPA19104 United States

A tunable U-slot microstrip patch antenna has two different antenna substrates operating around 5.4GHz. This design employs the BST material manganese-doped Ba0.8Sr0.2TiO3 soft ferroelectric thin films with relative d... 详细信息

ISBN: (纸本)9798350341140

关键词： BST Ferroelectric Frequency Tuning U-slot Antenna

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Analysis and control of complex cyber-physical networks

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Asian Journal of Control 2022年第2期24卷 495-497页

作者： Wen, Guanghui Jalili, Mahdi Ren, Wei Cao, Yongcan Du, Haibo Chen, Guanrong Research Center for Complex Systems and Network Sciences School of Mathematics Southeast University Nanjing China School of Engineering RMIT University MelbourneVIC Australia Department of Electrical Engineering University of California RiversideCA United States Department of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX United States School of Electrical Engineering and Automation Hefei University of Technology Hefei China Department of Electrical Engineering City University of Hong Kong Hong Kong

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Design and implementation of intelligent LiDAR SLAM for autonomous mobile robots using evolutionary normal distributions transform

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Soft Computing 2024年第6期28卷 5321-5337页

作者： Huang, Hsu-Chih Xu, Sendren Sheng-Dong Lin, Hsien-Chan Xiao, Yuan-Sheng Chen, Yu-Xiang Department of Electrical Engineering National Ilan University Yilan260007 Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei106335 Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei106335 Taiwan

This paper presents a method that employs an evolutionary normal distributions transform (NDT) for simultaneous localization and mapping (SLAM) using light detection and ranging (LiDAR) for autonomous mobile robots. An adaptive inertia weight and two genetic operators were employed in the Taguchi-based whale optimization algorithm (WOA) to improve the search diversity and avoid local optima. NDT was used to model the environment of differential-drive mobile robots and WOA was applied to optimize the scan matching for the robotic SLAM problem. The NDT-WOA determines the SLAM pose estimation using sensed data from the physical world. A nonholonomic mobile robot was steered to achieve the NDT-WOA SLAM task with the derived robot kinematics and actuator dynamics. The proposed method was implemented in a TurtleBot3 Burger robotic development kit, which includes a single-board computer and an OpenCR control board. The Robot Operating System (ROS) was utilized to implement the evolutionary NDT-WOA SLAM system due to its flexibility, open source, and client library. Simulation and comparisons were conducted to illustrate the efficiency of the proposed NDT-WOA SLAM method compared to other SLAM paradigms. The experimental results show the effectiveness of the proposed evolutionary NDT-WOA SLAM for autonomous mobile robots. The results could have theoretical and practical significance for robotics research. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Mobile robots

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Periodic Fisher-Scoring Algorithm with Applications for DOA Estimation in Seismic Arrays 26

Periodic Fisher-Scoring Algorithm with Applications for DOA ...

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26th International Conference on Information Fusion, FUSION 2023

作者： Khatib, Malaak Ben-Horin, Yochai Radzyner, Yael Rosenblatt, Jonathan D. Routtenberg, Tirza Ben-Gurion University of the Negev School of Electrical and Computer Engineering Beer Sheva Israel Soreq Nuclear Research Center Yavne Israel Faimatic Israel Princeton University Department of Electrical and Computer Engineering PrincetonNJ United States

ISBN: (纸本)9798890344854

In many practical parameter estimation problems, such as phase, frequency, and direction-of-arrival (DOA) estimation, the observation model is periodic with respect to the unknown parameters, and thus, the appropriate estimation criterion is periodic in the parameter space. However, iterative estimation methods, such as the Fisher-Scoring method, do not take into consideration the periodic information in order to improve the accuracy of the estimation. In this paper, we present a new iterative method - periodic Fisher-Scoring, which takes into account the signal's periodic properties through the utilization of the cyclic Cramér-Rao bound (CRB). The cyclic CRB is a lower bound on the mean cyclic error (MCE) of unbiased estimators and, thus, is more appropriate for the derivation of the iterative method. In addition, the periodic Fisher-Scoring method uses the modulo 2 π operator at each iteration. Simulation results for DOA estimation in seismic arrays show that the proposed periodic Fisher-Scoring estimator has a lower MCE compared to the conventional Fisher-Scoring estimator. The performance improvement is more significant around the edges of the range [-π,π] and under the misspecified model, i.e. under the mismatched assumption of white noise. We also show that the periodic Fisher-Scoring estimator achieves the cyclic CRB much faster than the CRB. © 2023 International Society of Information Fusion.

关键词： Iterative methods

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