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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Sun, Peihao Zhu, Ming Zhang, Yifei Chen, Tian Zheng, Zewei School of Aeronautic Science and Engineering Beihang University Beijing China Institute of Unmanned System Beihang University Beijing China School of Electronic and Information Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9798350316308

This study presents a novel trajectory tracking controller for a stratospheric airship, focusing on event-triggered control and prescribed performance. The proposed controller, based on the framework of prescribed performance backstepping method, combines a second-order derivative filter and a radial basis function neural network. The controller design incorporates an event-triggered strategy to achieve prescribed performance objectives. The derivative filter addresses the computational complexity associated with the virtual control law, while the radial basis function neural network estimates unknown terms. Through Lyapunov analysis, the stability and non-Zeno behavior of the system are established. Simulation results confirm the effectiveness of the designed controller in achieving the desired trajectory tracking objectives. © 2023 IEEE.

关键词： Controllers

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An Bio-Inspired Improved Self-organized Fission-Fusion Control Algorithm for Heterogeneous UAV Swarm 12th

An Bio-Inspired Improved Self-organized Fission-Fusion Contr...

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12th China Conference on Command and Control, C2 2024

作者： Zhang, Xiaorong Wang, Qing Zhang, Zhilan Zhang, Xinrui Wang, Yufeng Ding, Wenrui School of Electronic Information Engineering Beihang University Beijing100191 China Institute of Unmanned System Beihang University Beijing100191 China Automation Science Electrical Engineering Beihang University Beijing100191 China Shen Yuan Honors College Beihang University Beijing100191 China

ISBN: (纸本)9789819777730

Due to the motion conflicts and environmental interference among entities in heterogeneous unmanned aerial vehicle (UAV) swarms, controlling algorithm for heterogeneous UAV swarms has become a challenging issue in the field of UAVs. However, compared to homogeneous UAV swarms, less attention is given to the research on swarm fission-fusion algorithms for the heterogeneous type with dynamic obstacles. Inspired by the interaction mechanism of starlings and the self-organized swarm motion of heterogeneous UAV swarms, this paper proposes a bio-inspired improved self-organized fission-fusion control algorithm for heterogeneous UAV swarm. First, inspired by the staring interaction mechanism, this paper designs an improved topological interaction mechanism for the heterogeneous swarm. Second, we establish the UAV model and dynamic model of the heterogeneous swarm, consisting fixed-wing UAVs and quadcopters. Then, this paper designs a fission-fusion control algorithm for heterogeneous swarms, achieving self-organizing fission-fusion motion for heterogeneous UAV swarms to track dynamic obstacles. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments. © Chinese institute of Command and Control 2024.

关键词： Aircraft control

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Multitarget gas alarm system for high-performance and anti-interference chemical warfare agents simulants detection

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Science China(Technological Sciences) 2025年第3期68卷 349-358页

作者： Yubin YUAN Qiang WU Menglong JIAO Haiyang WU Weihua LIU Xuming WANG Xiangrui BU Gong LI Chuanyu HAN Long HU Xin LI Xiaoli WANG Shool of Microelectronics School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’an710049China The Key Lab of Micro-nano Electronics and System Integration of Xi’an City Xi’an710049China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou310024China School of Automation and Information Engineering Xi’an University of TechnologyXi’an710048China Key Laboratory for Physical Electronics and Devices of the Ministry of Education Xi’an Jiaotong UniversityXi’an710049China School of Science Xi’an Jiaotong UniversityXi’an710049China

Chemical warfare agents(CWAs)can cause significant harm to health and even death in a very short time even when inhaled in small amounts(~100 mg min/m^(3)).Detection equipment based on conventional techniques,including gas chromatography-mass spectrometry,Raman spectroscopy,fluorescence spectroscopy,and ion mobility spectrometry,have the disadvantages of high cost,long detection time,and high power ***,portable,and convenient equipment for target CWAs detection under interference is a *** this study,we propose an alarm system comprising a multitype micro sensor array and a field-programmable gate array-based readout circuit for CWAs simulants *** common volatile organic compound,temperature,and water vapor interference,the proposed multitype sensor-based detection system realizes an alarm function in less than 20 s with thresholds of 1 ppm dimethyl methylphosphonate(DMMP),4.6 ppm 2,2'-dichlorodiethyl ether(DCE),and 20 ppm SO_(2).Furthermore,the proposed detection system was evaluated outside the laboratory and passed the wilderness test,demonstrating its reliability in the *** believe that the proposed alarm system will contribute to the development of intelligent,portable,low-cost,and anti-interference CWAs detection technology.

关键词： alarm system CWAs simulants surface acoustic wave sensor mixed gas anti-interference

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Parameter Identification of Lithium-ion Battery using Dragonfly Algorithm 25

Parameter Identification of Lithium-ion Battery using Dragon...

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25th IEEE China Conference on system Simulation Technology and its Application, CCSSTA 2024

作者： Tian, Jiaqiang Yin, Xinxiang Pan, Tianhong Zhang, Xu Yang, Duo Ni, Liping Anhui University School of Eelectrical Engineering and Automation Hefei China Anhui University of Science and Technology Institute for Advanced Research Hefei China Zhengzhou University School of Electrical Engineering Henan China Anhui JAC SinoEV Battery System Co. Ltd. Hefei China

ISBN: (纸本)9798350366600

Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for constructing the voltage error evaluation function according to the first-order RC model. The DA is used for model parameter identification. The estimation effects of Particle Swarm Optimization (PSO) and Ant Lion Optimizer (ALO) are compared. The experimental results show that the proposed DA parameter identification algorithm has higher estimation accuracy. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Fixed-Time Predefined Performance Platoon Formation Control of Automated Vehicles with Uncertain Disturbances 8

Fixed-Time Predefined Performance Platoon Formation Control ...

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8th IEEE International Conference on Intelligent Transportation engineering, ICITE 2023

作者： Zhang, Yifei Sun, Yang Chen, Tian Zheng, Zewei Zhu, Ming School of Electronic and Information Engineering Beihang University Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Institute of Unmanned System Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9798350314212

This paper addresses the fixed-time predefined performance platoon formation control problem of automated vehicles with the consideration of uncertain disturbances. First, a general platoon formation control framework is developed. Then, the transformed errors are designed to make sure the predefined performance requirement is satisfied. Furthermore, the radial basis function neural network is introduced to deal with uncertain disturbances, which accommodates unmodelled dynamics and unknown external disturbances. To this end, the fixed-time stability of the whole closed-loop system is proved theoretically, and simulation results are given to illustrate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Radial basis function networks

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Practical Distance-Based Formation Stabilization and Tracking of Nonholonomic Multi-agent systems 7th

Practical Distance-Based Formation Stabilization and Tracki...

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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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STARTUP ANALYSES OF A HELIUM-XENON GAS-COOLED REACTOR 30

STARTUP ANALYSES OF A HELIUM-XENON GAS-COOLED REACTOR

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30th International Conference on Nuclear engineering, ICONE 2023

作者： Ma, Yugao Bao, Hui Lu, Jiahao Ding, Shuhua Zhang, Meng Yang, Xiaolong Deng, Jian Zhang, Muhao Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

ISBN: (纸本)9784888982566

The Helium-Xenon (He-Xe) gas-cooled reactor uses a He-Xe gas mixture to remove the heat from the reactor core. It has the characteristics of a long life-cycle, simple operation, and high power-mass ratio, which has an excellent application prospect in the field of Space Reactors Power systems. The high operation temperature distinguishes the He-Xe gas-cooled reactor from the traditional reactor in reactivity feedback characteristics. Except for the Doppler effect of the fuel and monolith, the thermal expansion also introduces reactivity feedback during reactor operation. In this work, reactivity feedback characteristics, steady-state characteristics, and transient characteristics of a hundred-kilowatt-level He-Xe gas-cooled reactor (Submersion-Subcritical Safe Space reactor, S4) were analyzed. The Doppler feedback characteristics and thermal expansion feedback coefficients of fuel, matrix, and reflector from the cold to the hot state of the S4 reactor core were calculated based on the reactor Monte Carlo code (RMC). The results show that the S4 reactor core is mainly affected by the fuel Doppler effect and the matrix thermal expansion effect. Furthermore, the temperature distributions of fuel and He-Xe gas of the S4 reactor were calculated using the He-Xe reactor transient analysis code (HXRTRAN). The transient characteristics of the S4 reactor core when different reactivity was introduced were analyzed. This study may provide a reference for the operation state of the He-Xe gas-cooled reactor. © 2023 by JSME.

关键词： Helium

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Design and Control of Continuous Jumping Gaits for Humanoid Robots Based on Motion Function and Reinforcement Learning

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Procedia Computer Science 2024年 250卷 51-57页

作者： Zida Zhao Shilong Sun Haodong Huang Qingbin Gao Wenfu Xu State Key Laboratory of Robotics and System (HIT) Harbin Institute of Technology Harbin Heilongjiang China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China

Continuous jumping of humanoid robots is a challenging problem that requires appropriate gait and force control for the robot to achieve. Reinforcement learning (RL) has been applied to the motion control of humanoid robots and has achieved significant progress. However, traditional RL control methods primarily rely on designing reward signals to generate human-like movements, and it requires developing complex reward signals for continuous jumping, resulting in limited actions and suboptimal jumping performance. To address this issue, we have designed motion functions for humanoid continuous jumping and incorporated them into the RL framework to obtain desired human-like continuous jumping actions. Furthermore, two different jumping gaits are designed to investigate the jumping effects produced by different jumping functions: bent-knee jumping (BJ) and straight-knee jumping (SJ). BJ is a typical jumping style where the legs flex during the jumping process to accumulate energy, enabling higher explosive power. SJ is more suitable for tasks requiring quick responses, as the legs remain upright during the jump, providing faster reaction speed. The performance in continuous jumping tasks has been evaluated by comparing the effects of training with different jumping functions. This research has particular guidance for improving the jumping ability of robots and enhancing the stability and efficiency of humanoid continuous jumping.

关键词： Continuous jumping gaits Humanoid robots Motion function Reinforcement learning

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NONLINEAR STEAM GENERATOR FEEDWATER system IDENTIFICATION BASED ON WAVELET NEURAL NETWORK 10

NONLINEAR STEAM GENERATOR FEEDWATER SYSTEM IDENTIFICATION BA...

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10th International Symposium on Test automation and Instrumentation, ISTAI 2024

作者： Wang, Hongrui Yuan, Mingzhe Zhang, Pengbin Xing, Kunpeng Guangzhou Institute of Industrial Intelligence Guangzhou China Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China China Nuclear Power Engineering Co. Ltd. Shenzhen China

ISBN: (纸本)9781837242672

Steam generator is the key equipment in the large and complex nuclear power plant, and its water supply system has the characteristics of time-varying, large delay, nonlinear. In this paper, a segmented linearized model based on wavelet neural network is developed for a steam generator feedwater system of a nuclear power plant. All the data of the automation stages of the steam generator, which are steam flow rate, feedwater flow rate and liquid level from 20% load to 100% load, are collected and divided into six stages based on the characteristics of the data. For the first four stages of data, the feedwater system was modelled using the Hammerstein-Wiener method based on wavelet neural network, which was used as the nonlinear input and nonlinear output module of Hammerstein-Wiener. And for the remaining two stages of data, the nonlinear autoregressive models based on with exogenous (ARX) inputs model approach was modelled using nonlinear ARX as the underlying framework of wavelet neural network. The proposed model can be used for model predictive control to switch between different models based on load changes. Through the verification of simulation experiments, the built model can accurately reflect the trend of actual data, and the predicted values have high accuracy and reliability. © The Institution of engineering & Technology 2024.

关键词： Nuclear power plants

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