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From Plant Modeling to Narrative Science:Growing and Enjoying Scientific Fruits Naturally and Humanistically

IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2522-2524页

作者： Fei-Yue Wang IEEE Macao University of Science and Technology Macao 999078China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

Dear Editor,Modeling is the first and essential step for control and automation,and large models,from current Chat GPT or large language models(LLMs)to future large knowledge models of knowledge automation,would be th... 详细信息

关键词： smart knowledge automation

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Secure Encoding Scheme for Consensus of Second-order Multi-Agent systems 41

Secure Encoding Scheme for Consensus of Second-order Multi-A...

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第41届中国控制会议

作者： Bingya Zhao Ya Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

We consider the problem of consensus of a second-order multi-agent system in the situation where an eavesdropper tends to impact the security of the network.A secure encoding scheme that guarantees both consensus and security of the multiagent network is *** the network,the agents transmit messages to one another through digital channels,and there exists an eavesdropper whose aim is to overhear the state information of the agents in the *** of transmitting the states of themselves,the agents in the network send states of auxiliary systems to defend against the *** concept of topological entropy is utilized to restrict the eigenvalues of the encoding matrix.A sufficient condition is given to guarantee that the network achieves consensus,and the eavesdropper cannot get the accurate estimation of the state of any agent.A simulation example is given to show the performance of the agents and the eavesdropper under the designed encoding scheme.

关键词： Multi-agent system secure encoding scheme consensus topological entropy maximum transmission rate

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Model Predictive Tracking control for Rigid Manipulators with Disturbance Rejection 41

Model Predictive Tracking Control for Rigid Manipulators wit...

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第41届中国控制会议

作者： Yihui Lu Linyan Han Jinhao Liu Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A model predictive tracking control algorithm for rigid manipulators considering the existence of external time-varying disturbances is studied in this *** the field of manipulators,disturbances are *** the influence of disturbances will lead to poor control accuracy and even *** a two-degree-of-freedom(2-DoF) rigid manipulator,a composite algorithm combing model predictive control(MPC) and a generalized proportional integral observer(GPIO) is *** the proposed method,feedback linearization technology is used to decouple the *** order to improve the ability of disturbance rejection,a GPIO is used to estimate the lumped disturbances and the estimated values are added to the control law by feedforward *** is conducted to validate the proposed algorithm.

关键词： Model Predictive control(MPC) Manipulator Generalized Proportional Integral Observer(GPIO) Feedback Linearization

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Intra-hour PV Power Forecasting based on Multi-source Data and PSC-SVR Model 41

Intra-hour PV Power Forecasting based on Multi-source Data a...

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第41届中国控制会议

作者： Kai Wang Weijing Dou Haikun Wei Kanjian Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Accurate photovoltaic power forecasting(PVPF) can ensure the stability of grid operation and the reliability of economic ***,PV power generation is greatly affected by weather conditions,thus more external information needs to be combined to improve the forecasting *** on the measured data and NWP data,this paper proposes a PSC-SVR model to forecast the intra-hour PV *** model consists of PV physical model(PSC) and support vector regression(SVR).PSC converts the irradiance as a priori feature of the model,including calculating the sun position,irradiance separation and transposition *** is used for the two-stage data fusion of NWP power modeling and power *** method was verified on 4 power stations in the public data set *** forecasting PV power in the next one hour,the average RMSE/MAE of all stations is 1.927 MW/1.167 MW,which decreases by 40%/55% compared with persistent model,6%/7% compared with NWP correction forecasting method,9%/13% and 32%/34% compared with the single measured data and single NWP *** above results show the effectiveness of our proposed model in multi-source data fusion and PV power forecasting.

关键词： Photovoltaic Power Forecasting NWP Data Fusion Physical Model Support Vector Regression

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A Hierarchical Formation-Containment control Scheme for Second-Order Multi-agent systems 7th

A Hierarchical Formation-Containment Control Scheme for Sec...

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

作者： Cao, Yue Wang, Xiangyu Chen, Yangyang School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9789819733231

In this paper, a hierarchical formation-containment control scheme is proposed for second-order multi-agent systems. The proposed hierarchical scheme decouples the control task into two layers, i.e., reference signal generator and agents’ tracking controllers. First, a reference signal generator is designed in Layer 1 for leader agents and follower agents, respectively, to produce the formation reference signals and containment reference signals, whose outputs "achieve" formation-containment asymptotically. Second, tracking controllers are designed in Layer 2 for each agent to track the reference signal. The proposed hierarchical formation-containment scheme realizes formation-containment asymptotically. The simulations are performed to validate the effectiveness and practicality of the scheme. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Interaction Torque Estimation for Robotic Manipulators under Low-Speed Condition 41

Interaction Torque Estimation for Robotic Manipulators under...

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第41届中国控制会议

作者： Yufeng He Wenwu Zhu Linyan Han Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper studies the interaction torque estimation method of the rigid robotic manipulator under the low-speed ***,a nonlinear friction model is established to analysis the influence of *** the noise into consideration,a least square identification method is ***,a finite-time extended state observer is established to estimate the interaction torque,which is capable of estimating time-varying *** stability of the system is demonstrated based on the Lyapunov *** results are given to show the effectiveness of the proposed method.

关键词： Force estimation Robotic manipulator Stribeck friction Finite-time observer

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Continuous Non-Singular Terminal Sliding Mode control for High Pressure Common Rail systems Using a FTDO 41

Continuous Non-Singular Terminal Sliding Mode Control for Hi...

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第41届中国控制会议

作者： Zheng Yuan Chen Dai Hao Sun Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

High pressure common rail(HPCR) technology has been widely applied in diesel *** tracking speed and the steady-state fluctuations of the rail pressure determine the performance of the HPCR *** this paper,the fuel injection disturbance which has a main impact on rail pressure fluctuations is fully *** on fluid dynamics and Newtonian mechanics,a nonlinear model of the HPCR system is *** order to suppress the fuel injection disturbance,a finitetime disturbance observer(FTDO) based continuous non-singular terminal sliding mode controller(CNTSMC+FTDO) is designed based on the three-step analysis *** is proved that the system tracking error can converge to the equilibrium point in a finite ***,a group of simulations and experiments are conducted in Simulink and the more realistic AMESim environment respectively and the results verify the effectiveness and feasibility of the proposed algorithm.

关键词： High pressure common rail Non-singular terminal sliding mode FTDO Rail pressure control AMESim

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Pylon Reconstruction Based on NeRF 14

Pylon Reconstruction Based on NeRF

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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Hu, Zijian Wang, Chenxing Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350361889

In this paper, we propose a pylon reconstruction method based on Neural Radiance Fields (NeRF) technology. The advantage of this method lies in its ability to reconstruct pylons from images, with a multi-view model maintaining good performance even under complex lighting and occlusion conditions. We demonstrate the process of using NeRF to reconstruct electric power towers through experiments. During the experimental process, we collect images of electric power towers from different environments and angles, then apply NeRF to process these images, using deep learning to learn and generate a network model capable of expressing the scene. The experimental results show that our method can complete the reconstruction of scenes with only image inputs, and the reconstructed models have a certain accuracy in terms of geometric details and textures. © 2024 IEEE.

关键词： Deep learning

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Time-varying formation tracking control of high-order multi-agent systems with multiple leaders and multiplicative noise

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Science China(Information Sciences) 2024年第12期67卷 191-207页

作者： Ruru JIA Xiaofeng ZONG Qing WANG College of Artificial Intelligence Nankai University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Science and Electrical Engineering Beihang University

This work discusses the time-varying formation(TVF) tracking control problem of high-order multi-agent systems(MASs) with multiple leaders and multiplicative measurement noise. With the help of Lyapunov function tools and stochastic analysis methods, the TVF tracking protocol with multiple leaders and multiplicative noise is developed based on the relative state measurements, where followers are driven to realize the target TVF while tracking the convex combination formed by multiple leaders. Then, the TVF tracking problem is converted into the mean square asymptotic stability problem of a stochastic differential equation(SDE); sufficient conditions related to the control gains are given by stabilizing the corresponding stochastic system. Moreover, a TVF tracking algorithm is presented to outline the steps of protocol ***, the theoretical results are illustrated in terms of simulation examples.

关键词： multi-agent systems multiple leaders multiplicative measurement noise stochastic differential equation formation tracking control

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Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal Location Module 42

Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal...

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42nd Chinese control Conference, CCC 2023

作者： Xu, Dapeng Lu, Xiaobo Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

Fall events have unique dynamic features, which are not fully utilized by existing fall detection methods. Based on video understanding, we propose Fall-LSTM to learn such features pertinently without additional inputs. Fall-LSTM is composed of CNN-LSTM framework and two excitation modules i.e., Spatial Attention Module (SAM) and Temporal Location Module (TLM). SAM provides spatial constraints on motion for feature layers through foreground extraction and spatial pooling. TLM emphasizes frames with high probability of fall events to LSTM by inferring the rate and trend of motion in clips. Experimental results show that our proposed modules significantly improve the performance of LSTM model, outperforming the state-of-the-art methods on two public Fall Detection Datasets i.e., Le2i and UR. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Location

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