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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Gao, Yan Wei, Donghui Bai, Chenggang Quan, Quan School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

The multicopter formation is widely used in many different complex circumstances. And the semi-autonomous multicopter formation controlled with a single pilot on the ground draws people’s attention due to the great adaptability to various kinds of environments. In this paper, we focus on the problem of passing through narrow channels with semi-autonomous multicopter formation. Similar to the definition for a single multicopter, the altitude hold mode for the multicopter formation is defined first. Then, the formation decision-making and formation low-level control of the altitude hold mode are proposed one by one. Finally, a hardware-in-the-loop simulation and a real experiment are performed with four multicopters to pass through a narrow channel. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision making

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A Deep Learning Based Personal Authentication Method Using sEMG Signal 41

A Deep Learning Based Personal Authentication Method Using s...

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第41届中国控制会议

作者： Lina Tong Mingjia Zhang Daisong Liu Hanghang Ma Yuxiang Zhang Liang Peng School of Mechanical Electronic & Information Engineering Chinese University of Mining and Technology-Beijing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChina Academy of Science

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Personal authentication means that the relevant system confirms whether the identity of the user is real,legal and unique.A safe and convenient personal authentication method is a core for guarantee the security of our information and *** Electromyography(sEMG),which exists on the surface of the skin,is a good signal to achieve personal authentication,for it is difficult to be extracted and *** this paper,a new personal authentication method using forearm sEMG is ***,8-channel sEMG signals are recorded by Myo armband that is placed on right forearm of 14 subjects who perform the same hand open ***,two different deep learning models are presented to classify the *** multi-layers Convolution Neural Network(ML-CNN) and two stages Long Short Term Memory(2 s-LSTM) Network can achieve accuracy of 97.50% and 93.60% respectively,shows it is feasible to achieve the goal of personal *** the time cost of ML-CNN is higher than the 2 s-LSTM,both are lower than human reaction *** the architecture of ML-CNN is more suitable to achieving the goal of personal authentication.

关键词： Personal Authentication Surface Electromyography(sEMG) Myo multi-layers Convolution Neural Network(CNN) LSTM Network

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Development of a PM Spherical Actuator with Tiltable Stator for High Torque Density

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IEEE Transactions on Transportation Electrification 2025年

作者： He, Xinghua Xiang, Pengjie Yan, Liang Yang, Xuxu Liu, Xiaoshuai Du, Nannan Bu, Suwan Yan, Guishan Ai, Chao Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Ningbo Institute of Technology Ningbo315800 China Sun Yat-Sen University School of Intelligent Systems Engineering Shenzhen518000 China Yanshan University School of Mechanical Engineering Qinhuangdao066004 China

Spherical actuators are active joints that rotate around three directions and are more compact than conventional joints using multiple single-axis motors connected in series. However, spherical electromagnetic actuators have low torque density, particularly in tilt directions, hindering practical applications. The essential reason is that their stator and rotor are misaligned after tilting, which not only reduces the electromagnetic torque but also introduces restoring torques. To enhance torque density, this paper proposes a 3-DOF permanent magnet spherical actuator with a tiltable stator. The relative positions of the stators and rotors of each actuation unit remain unchanged after tilting, maintaining high output torque and allowing large tilting angles, and rotating and tilting torques are decoupled. We introduce the working principle of the proposed actuator and establish its basic structure. Two-dimensional magnetic field finite element analysis and conformal transformation are combined to simplify three-dimensional magnetic field computations. The optimized parameters for the tilting unit are obtained. Finally, a prototype is fabricated and experimentally tested. The proposed spherical actuator yields a tilt torque exceeding 8 Nm and a rotation torque of 7.34 Nm, corresponding to a torque density of 1.75 Nm/kg for tilt and 1.6 Nm/kg for rotation relative to the entire actuator. © 2015 IEEE.

关键词： Spheres

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Uncertainty and Reliability Analysis of Neural Networks Based Soft-sensors with Applications in Wastewater Treatment

Uncertainty and Reliability Analysis of Neural Networks Base...

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2022 Chinese automation Congress, CAC 2022

作者： Liu, Yiqi Yuan, Jingyi Huang, Daoping Key Laboratory of Autonomous Systems and Networked Control Ministry of Education The School of Automation Science & Engineering South China University of Technology Guangzhou510640 China

ISBN: (纸本)9781665465335

To overcome the transparency and interpretability issues of neural network-based soft sensing, a data-driven framework by combining neural network prediction models and sensitivity analysis methods is constructed in this paper, with application in wastewater treatment plant analysis. The results show that readily biodegradable substrate effluent (SS-e) and NH4+ + NH3 nitrogen effluent (SNH-e) are both important input factors affecting the difficult-to-measured effluent quality, chemical oxygen demand (COD), by resorting to PAWN sensitivity analysis and four neural network models. In addition, four neural network models worked together with bilateral sensitivity analysis for the input perturbation analysis, which shows that the addition of Gaussian perturbation to SS-e and flow rate influent (Q-in) has a greater effect on the prediction which results large fluctuations of output results. Finally, the effectiveness of this framework is confirmed based on above results. © 2022 IEEE.

关键词： Sensitivity analysis

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Secure output synchronization of heterogeneous multi-agent systems against false data injection attacks

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science China(Information sciences) 2022年第6期65卷 142-154页

作者： Shicheng HUO Dalin HUANG Ya ZHANG School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Cyber Science and Engineering Southeast University

This paper studies secure output synchronization for heterogeneous multi-agent systems against false data injection(FDI) attacks. Both the sensors and actuators of agents may be injected into FDI *** mitigate the malicious impact of these attacks on synchronization performance, a desired reference model,which is combined with an auxiliary system, is first designed for each agent to simulate its normal system dynamics. Then, based on this reference model, a state feedback cooperative controller and a static output feedback cooperative controller, which consist of adaptive compensators, are proposed, respectively. The integrated control protocols can ensure that the output synchronization error is small by adjusting some designed parameters even in the presence of FDI attacks. An illustrative example is employed to demonstrate the effectiveness of the proposed method.

关键词： output synchronization false data injection attacks adaptive compensators heterogeneous multi-agent systems secure control

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Deployment of optoelectronic devices based on improved NSGA-II

Deployment of optoelectronic devices based on improved NSGA-...

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2023 International Conference on Mechatronic engineering and Artificial Intelligence, MEAI 2023

作者： Gong, Hua Sui, Guoshuang Xu, Ke Sun, Wenjuan Shi, Yiying College of Science Shenyang Ligong University Shenyang110159 China Liaoning Provincial Key Laboratory of Intelligent Optimization and Control of Ordnance Industry Liaoning Shenyang110159 China School of Automation and Electrical Engineering Shenyang Ligong University Liaoning Shenyang110159 China

ISBN: (纸本)9781510674608

In order to improve the security of the defended targets in our region and efficiently utilize various types of optoelectronic devices, the research is conducted on optoelectronic devices deployment within the region. With the objectives of maximizing the protection effectiveness and minimizing devices operational cost, a multi-objectives optimization model is established by considering constraints such as devices-target visibility conditions and device types, quantities, etc. Non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ) improved by Q-learning is designed to solve the model. To address the difficulty of fixed parameter settings adapting to dynamic changes, Q-learning is adopted to adaptively adjust the crossover probability and variation probability. In order to search for Pareto front solutions that are close to the global optimal more efficiently. The correctness of the model and the effectiveness of the algorithm are verified through simulation examples. © 2024 SPIE.

关键词： Optoelectronic devices

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Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties:Fundamental Variance Bounds

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Journal of Systems science & Complexity 2021年第5期34卷 1858-1878页

作者： QI Tian CHEN Jie School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked ControlSouth China University of TechnologyGuangzhou 510640China Department of Electrical Engineering City University of Hong KongHong KongChina

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative *** authors consider multi-input,multi-output(MIMO)linear time-invariant systems subject to multiple static,structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square *** the stochastic control framework,this problem can be considered as one of optimal control under state-or input-dependent random noises,while in the networked control setting,a problem of networked feedback stabilization over lossy communication *** authors adopt a mean-square small gain analysis approach,and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output *** single-input,single-output(SISO)systems,the condition provides an analytical bound,demonstrating explicitly how plant unstable poles,nonminimum phase zeros,and time delay may impose a limit on the uncertainty variance required for mean-square *** MIMO minimum phase systems with possible delays,the condition amounts to solving a generalized eigenvalue problem,readily solvable using linear matrix inequality optimization techniques.

关键词： Mean-square small gain theorem multiplicative stochastic uncertainty networked control

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Sampled-Data Semi-Global Practical Tracking for Uncertain Euler-Lagrange Systems

Sampled-Data Semi-Global Practical Tracking for Uncertain Eu...

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2022 Chinese automation Congress, CAC 2022

作者： Zeng, Kaiji Liu, Wei South China University of Technology Ministry of Education School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked Control Guangzhou510641 China

ISBN: (纸本)9781665465335

We investigate a sampled-data tracking control for uncertain Euler-Lagrange systems in this paper. What makes our result interesting is that our system and exosystem encompass some uncertain parameters that belong to some compact domain that can be specified arbitrarily large. To handle the uncertainties in both the Euler-Lagrange systems and the exosystem, we need to resort to not only the adaptive control technique but also the internal model method. By proposing a sampled-data control law, we solve the problem with guaranteed tracking performance, that is, the tracking errors can converge exponentially, by any fast specified rate, to any small specified neighborhood of the origin. © 2022 IEEE.

关键词： Lagrange multipliers

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SOM Neural Network Based Gaussian Mixture PHD Algorithm for Multi-Sensor Multi-Target Tracking

SOM Neural Network Based Gaussian Mixture PHD Algorithm for ...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Yujie Zheng, Hongwei Zhang, Zheng Yu, Jianglong Hua, Yongzhao Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In the multi-sensor multi-target tracking (MSMTT) problem, the matching of the measurements and the targets will generate a huge computational burden, resulting in an unsatisfactory real-time performance of the maneuvering targets tracking. In order to reduce the computational burden, this paper proposes a self-organizing feature map (SOM) neural network based Gaussian mixture probability hypothesis density algorithm (SOM-GMPHD). Firstly, a distributed filtering MSMTT algorithm based on SOM neural network is proposed. The distributed SOM-GMPHD algorithm (DSOM-GMPHD) has two fusion steps. Secondly, to further reduce the computational complexity, a centralized SOM-GMPHD algorithm (CSOM-GMPHD) with only one-step fusion is proposed. The computational complexity analysis of the existing MSMTT algorithms (DGMPHD and CGMPHD) and the proposed SOM-GMPHD algorithms are carried out in this paper. Finally, the effect of the proposed algorithms is evaluated in the simulation experiment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Self organizing maps

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UAV Path Planning from Human Demonstrations Using Inverse Reinforcement Learning

UAV Path Planning from Human Demonstrations Using Inverse R...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Xu, Zhiang Dong, Jin Hua, Yongzhao Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In UAV path planning tasks, classical algorithms can only solve the tasks where environment is knowable and can be changed into mathematical model. For the tasks with unknown environment information is difficult to solve. However, such tasks can be easily solved by human. In this paper, we first bulid a UAV path planning environment and train the agent with deep reinforcement learning as human demonstration. Then, we use inverse reinforcement learning algorithm and processed human demonstrations to learn human policy. Finally, we test the trained policy in path planning tasks to verify the feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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