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Piezoelectric Field Effect Transistors(Piezo-FETs)for Bionic MEMS Sensors:A Literature Review

Journal of Bionic engineering 2024年第6期21卷 2717-2729页

作者： Chang Ge Huawei Chen The Department of Electrical and Computer Engineering The University of British ColumbiaVancouverBCV6T 1Z4Canada School of Mechanical Engineering and Automation Beihang UniversityBeijing100191China

This paper presents a literature review exploring the potential of piezoelectric field-effect transistors(piezo-FETs)as bionic microelectromechanical systems(MEMS).First,piezo-FETs are introduced as bionic counterparts to natural mechanoreceptors,highlighting their classic configuration and working ***,this paper summarizes the existing research on piezo-FETs as sensors for pressure,inertial,and acoustic *** selections,design characteristics,and key performance metrics are reviewed to demonstrate the advantage of piezo-FETs over traditional piezoelectric *** identifying the limitations in these existing studies,this paper proposes using bionic piezoelectric coupling structures in piezo-FETs to further enhance the sensing capabilities of these artificial *** validated manufacturing methods for the newly proposed piezo-FET structures are also reviewed,pointing out a novel,feasible,and impactful research direction on these bionic piezoelectric MEMS sensors.

关键词： Bionic MEMS Piezoelectric field-effect transistors Tactile sensor Multi-axis accelerometer Directional microphone

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Effective distributed algorithm for solving linear matrix equations

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Science China(Information Sciences) 2023年第8期66卷 265-266页

作者： Songsong CHENG Jinlong LEI Xianlin ZENG Yuan FAN Yiguang HONG Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Department of Control Science and Engineering Tongji University Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...

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Observer design and interval estimation of time-delay discrete-time linear systems with external disturbance and measurement noise

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control Theory and Technology 2024年第1期22卷 69-80页

作者： Junqi Yang Jianhao Xie Feiyang Liu School of Electrical Engineering and Automation Henan Key Laboratory of Intelligent Detection and Control of Coal Mine EquipmentHenan Polytechnic UniversityJiaozuo454003HenanChina

For a class of time-delay discrete-time linear systems with external disturbance and measurement noise, the interval estimation problems of state and measurement noise are investigated in this paper. First, the system state together with the time-delay term and measurement noise is augmented as a new state, and a singular system is then constructed. Subsequently, a kind of decoupling technique is employed to eliminate the effect of external disturbance, and an observer is designed to simultaneously estimate the system state and measurement noise. Based on the estimated state and measurement noise, the interval estimations of system state and measurement noise are obtained by reachability analysis technique. Finally, the effectiveness of the proposed method is verified by a four-tank liquid level system.

关键词： Interval estimation Time-delay system Observer design Reachability analysis

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Guest Editorial: EV charging impacts on power system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2024年第6期18卷 1091-1094页

作者： [Anonymous] Department of Electrical Engineering and Automation Aalto University Espoo Finland School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical Engineering São Paulo State University Ilha Solteira Brazil Electrical Engineering Department Sharif University of Technology Tehran Iran School of Industrial Engineering University of Castilla‐La Mancha Ciudad Real Spain

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Autonomous embodied navigation task generation from natural language dialogues

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Science China(Information Sciences) 2025年第5期68卷 119-132页

作者： Haifeng XU Yongchang LI Lumeng MA Chunwen LI Yanzhi DONG Xiaohu YUAN Huaping LIU Department of Automation Tsinghua University School of Physics and Electronic Information Yantai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Computer Science and Technology Tsinghua University

Robots are increasingly being deployed in densely populated environments, such as homes, hotels, and office buildings, where they rely on explicit instructions from humans to perform tasks. However, complex tasks often require multiple instructions and prolonged monitoring, which can be time-consuming and demanding for users. Despite this, there is limited research on enabling robots to autonomously generate tasks based on real-life scenarios. Advanced intelligence necessitates robots to autonomously observe and analyze their environment and then generate tasks autonomously to fulfill human requirements without explicit commands. To address this gap, we propose the autonomous generation of navigation tasks using natural language dialogues. Specifically, a robot autonomously generates tasks by analyzing dialogues involving multiple persons in a real office environment to facilitate the completion of item transportation between various *** propose the leveraging of a large language model(LLM) through chain-of-thought prompting to generate a navigation sequence for a robot from dialogues. We also construct a benchmark dataset consisting of 625 multiperson dialogues using the generation capability of LLMs. Evaluation results and real-world experiments in an office building demonstrate the effectiveness of the proposed method.

关键词： proactive robot robot navigation service robot large language model

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Human Cognitive Learning in Shared control via Differential Game With Bounded Rationality and Incomplete Information

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 5141-5152页

作者： Wu, Huai-Ning Jiang, Xiao-Yan Wang, Mi Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Hangzhou International Innovation Institute of Beihang University Hangzhou311115 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China

Since human beings are of limited reasoning ability as well as the machines do not usually know human intentions, how to learn human cognitive levels in shared control to enhance the machines’ intelligence is a challenging issue. In this study, this issue is addressed in the context of human–machine shared control for a class of human-in-the-loop (HiTL) systems based on a differential game with bounded rationality and incomplete information. Initially, we formulate the human–machine shared control problem as a two-player nonzero-sum linear quadratic dynamic game (LQDG), where the weighting matrix of the cost function representing the human intention is unknown for the machine. To model the human bounded rationality, the level-k (LK) approach is employed to set up the LK control policies of two players performing the corresponding steps of strategic thinking. To infer the human intention, an online adaptive inverse optimal control (IOC) algorithm is then developed by using the system state data, so that the control policies of different cognitive levels can be computed. In addition, a reinforcement learning method is proposed for the machine to identify the distribution of the human cognitive levels while providing a proactive collaborative control to assist the human in a probabilistic switching way. Finally, simulation results on a cooperative shared control driver assistance system (DAS) illustrate the efficacy of the proposed approach. © 2024 IEEE.

关键词： Game theory

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Distributed Leaderless Optimal Output Consensus of Heterogeneous Multi-Agent Systems

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Journal of Systems Science & Complexity 2025年第2期38卷 671-690页

作者： ZHANG Liping ZHANG Huanshui XIE Lihua College of Electrical Engineering and Automation Shandong University of Science and Technology School of Control Science and Engineering Shandong University School of Electrical and Electronic Engineering Nanyang Technological University

The distributed optimal output synchronization problem for the leaderless heterogeneous multi-agent system with a general global cost function is investigated for the first time by linear quadratic(LQ) optimal control theory. Conventional algorithms for heterogeneous systems are quite complex, requiring the design of a virtual reference generator and the solving of regulation *** paper presents a novel distributed asymptotically optimal controller by incorporating the design of distributed observer and feedforward controller. A general form of the distributed controller is obtained by solving an augmented algebraic Riccati equation, which is parallel to classical optimal control theory. The optimal topology is an arbitrary directed graph containing only a spanning tree. It is shown that the proposed algorithms outperform the traditional consensus methods in the convergence speed by selecting proper observer gain matrices, and eliminate the reliance on the nonzero eigenvalues of Laplacian matrix. Simulation example further demonstrates the effectiveness of the proposed scheme and a faster superlinear convergence speed than the existing algorithm.

关键词： Distributed feedforward control heterogeneous systems leaderless output consensus optimal control

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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multiphysical analysis and motor design optimization. This article proposes a new method for thermal steady state modeling and analysis based on transfer learning (TL), which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on TL is developed: the model is pretrained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then, the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R^{2} and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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Linear active disturbance rejection control of fighter aircraft based on MADDPG algorithm

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International Journal of Systems, control and Communications 2025年第2期16卷 152-172页

作者： Lin, Yetong Ji, Yuehui Song, Yu Liu, Junjie Tianjin Key Laboratory for Control Theory and Applications in Complicated Industry Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China

To address nonlinearity, strong coupling, and disturbances in fighter aircraft attitude control, this paper proposes an intelligent control method based on multi-agent deep deterministic policy gradient (MADDPG) and linear active disturbance rejection control (LADRC). A three-channel LADRC controller estimates and compensates for disturbances, uncertainties, and coupling terms in real time. To overcome the dimensionality curse in multi-parameter optimization, an independent DDPG controller is assigned to each channel, ensuring cooperative control via reward sharing and enhancing dynamic response and disturbance rejection. Additionally, long short-term memory (LSTM) and self-attention mechanisms are integrated into the policy and value networks to improve representation and decision-making. A piecewise combined reward function mitigates sparse rewards. Simulations show that, compared to MADQN-based and traditional LADRC methods, the proposed approach achieves superior control performance and significantly reduces manual parameter tuning efforts. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Disturbance rejection

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A Review on Cybersecurity Analysis,Attack Detection,and Attack Defense Methods in Cyber-physical Power Systems

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 727-743页

作者： Dajun Du Minggao Zhu Xue Li Minrui Fei Siqi Bu Lei Wu Kang Li Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA School of Electronic and Electrical Engineering University of LeedsLeeds LS29JTUK IEEE

Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and *** timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems(CPPSs).This paper presents a comprehensive review of some of the latest attack detection and defense ***,the vulnerabilities brought by some new information and communication technologies(ICTs)are analyzed,and their impacts on the security of CPPSs are *** malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework,and their features and negative impacts are ***,two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed,and their benefits and drawbacks are ***,two current mainstream attack defense methods including active defense and passive defense methods are comprehensively ***,the trends and challenges in attack detection and defense strategies in CPPSs are provided.

关键词： Cyber-physical power systems security threat attack detection attack defense state estimation machine learning

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