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8th Renewable Power Generation Conference (RPG 2019)

作者： You Hu Jiajun Wang Bin Liu Zhen Li Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The grid-connected three-phase inverter is an indispensable part of the microgrid. The droop control is widely used in parallel inverters for high reliability and flexibility. The output impedance of droop controlled inverters plays an vital role in its stability. However, the sequence impedance model of grid-connected inverter is currently based on the grid side converter with a single current loop control exdluding the low-frequency dynamics similar in doubly fed induction generators. Both the droop control and voltage loop control greatly affect the stability of inverter, specifically in the low frequency response. This paper proposes a sequence impedance model of inverter, which considers the droop control and voltage and current dual closed-loop control using the harmonic linearization method in the frequency domain. The accuracy of the model is verified through comparing the measurement impedance value in simulation with the impedance value calculated in the sequence impedance model. The influence of control method on system impedance is verified by showing the difference between the single loop controlled inverter and droop control inverter.

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TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models

arXiv

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arXiv 2021年

作者： Yan, Tijin Zhou, Tong Zhan, Yufeng Xiaa, Yuanqing Key Laboratory of Intelligent Control Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

With the development of AIoT, data-driven attack detection methods for cyber-physical systems (CPSs) have attracted lots of attention. However, existing methods usually adopt tractable distributions to approximate data distributions, which are not suitable for complex systems. Besides, the correlation of the data in different channels does not attract sufficient attention. To address these issues, we use energy-based generative models, which are less restrictive on functional forms of the data distribution. In addition, graph neural networks are used to explicitly model the correlation of the data in different channels. In the end, we propose TFDPM, a general framework for attack detection tasks in CPSs. It simultaneously extracts temporal pattern and feature pattern given the historical data. Then extract features are sent to a conditional diffusion probabilistic model. Predicted values can be obtained with the conditional generative network and attacks are detected based on the difference between predicted values and observed values. In addition, to realize real-time detection, a conditional noise scheduling network is proposed to accelerate the prediction process. Experimental results show that TFDPM outperforms existing state-of-the-art attack detection methods. The noise scheduling network increases the detection speed by three times. Copyright © 2021, The Authors. All rights reserved.

关键词： Embedded systems

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Stabilization of a class of fractional order chaotic systems by nonlinear sliding mode

Stabilization of a class of fractional order chaotic systems...

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第37届中国控制会议

作者： Lijun Lin Yongzhi Sheng School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

This paper investigates the stabilization problem of a class of fractional order chaotic systems with unknown modeling uncertainties and external perturbations. A fractional nonlinear sliding surface is proposed, and a reaching control law is obtained to guarantee the stability of the fractional chaotic system in finite time with just a single control input. And the simulation results are given to demonstrate the efficacy of the proposed nonlinear sliding mode control method.

关键词： Fractional order Chaotic system Nonlinear sliding mode Stabilization

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Event-Triggered Networked Predictive controller Design for Linear systems with Communication Delay

Event-Triggered Networked Predictive Controller Design for L...

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第三十三届中国控制会议

作者： Di Wang Jian Sun Jie Chen School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479947249

This paper is concerned with the controller design for networked control systems(NCSs). A novel eventtriggered networked predictive control scheme is proposed to compensate for the network-induced delay and save network bandwidth. The closed-loop system is modeled as a switched system with time-varying delay. By constructing a common Lyapunov function, a sufficient stability condition is derived and presented in terms of linear matrix inequalities(LMIs). In order to prove the validity of the proposed method, both a simulation and an experiment are carried out. Both simulation results and experimental results show that this method can compensate for the network-induced delay actively and reduce the burden of the network significantly.

关键词： Networked control system,Networked predictive control,Event-triggered control,Lyapunov function

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Event-Triggered Extended Kalman Filter for UAV Monitoring system

Event-Triggered Extended Kalman Filter for UAV Monitoring Sy...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Yanmin Liu Xiaozhong Liao Zihao Wang Xi Chen Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

The unmanned aerial vehicles (UAVs) formation needs the frequent data-exchanging of individual's state between units for monitoring and instruction uploading from the ground station, which inevitably occupies huge communication bandwidth. This paper presents the extended Kalman filter (EKF) design based on the event-triggered strategy to get UAVs greatly relieved of the communication burden with guaranteed accuracy. The event-triggered strategy firstly selects only the state measurements containing innovational information for the purpose of filtering. Due to the nonlinearity of UAV system, the EKF is further applied to make full use of the information from the prior event-trigger strategy so as to enhance the performance of estimation. The proposed algorithm is verified on the physical UAVs regarding the estimation quality and communication rate, demonstrating the robust dynamic performance with effectively reduced communication rate.

关键词： Estimation Quaternions Unmanned aerial vehicles Monitoring Kalman filters Accelerometers Data models

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Time-Varying Sliding Mode Guidance with Impact Angle Constraints Against Nonmaneuvering Targets

Time-Varying Sliding Mode Guidance with Impact Angle Constra...

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第三十二届中国控制会议

作者： Yao Zhao Yongzhi Sheng Xiangdong Liu School of Automation Beijing Institute of Technology Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479900305

In this paper,a time-varying sliding model control(TVSMC) based guidance law against nonmaneuvering targets is proposed with impact angle *** algorithm is first designed for constant-speed interceptors to attack stationary and constant-velocity targets,and the global robustness of the system is ***,an adaptation strategy,adaptive time-varying sliding model control(ATVSMC),is adopted to deal with unknown but bounded disturbances by adjusting the switching gain *** analysis of the closed loop system is obtained through Lyapunov ***,numerical simulation results are presented to verify the effectiveness and robustness of the proposed guidance law.

关键词： Guidance Impact angle Time-varying sliding model control Robustness Adaptive

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H∞ Polytopic Filter Design for Nonlinear systems

H∞ Polytopic Filter Design for Nonlinear Systems

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第35届中国控制会议

作者： Yin Yu Zhen Li Jian Li Luyu Li Xiangdong Liu School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

This paper proposes an H polytopic lter design for a nonlinear system. Based on the polytopic approximation of the nonlinear system, the polytopic lter design is converted into a group of linear matrix inequalities（LMIs） so that the polytopic lter parameters can be effectively acquired by numerical convex optimization algorithms. At this stage, the tensor product（TP） model transformation is utilized to compute the polytopic approximation of the nonlinear system. Particularly, a new recti cation procedure is further developed to obtain a specific polytopic approximation with all the vertex systems being stable, which premises the solvability of the LMIs. The method is much easier to be implemented than traditional approaches such as the Hamilton-Jacobi inequality（HJI）-based methods. Simulation demonstrates the method is much less conservative than the existing method and has good estimation performance.

关键词： H_∞ lter nonlinear systems polytopic model tensor product model transformation

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A fast test and compensation system for optical encoders based on extreme learning machine — Fourier Neural Network

A fast test and compensation system for optical encoders bas...

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Jiachen Zhao Jie Chen Fang Deng Hongda Li Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China School of Automation Beijing Institute of Technology BeiJing

ISBN: (纸本)9781538629024

This paper describes fast test and compensation system for optical encoders. The resolution of system is 0.375", and it can measure the actual accuracy of an optical encoder in four minutes. Furthermore, a method called Extreme Learning Machine - Fourier Neural Network (ELM-FNN) are proposed to compensate the error. Fourier neural network (FNN) is chosen to fit the curve of the optical encoder's output, and the weights of FNN is calculated by Extreme Learning Machine (ELM). Experimental results demonstrate that ELM-FNN effectively improve the accuracy of the optical encoder. Compared to a back propagation neural network (BP net) and a standard FNN, ELM-FNN has advantages of higher accuracy and less training time.

关键词： Adaptive optics Optical computing Optical variables measurement Optical sensors Neural networks Ultraviolet sources Training

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Torque Compensation Model and Touchdown Detection Model of the Hydraulic Quadruped Robot controlled by VMC

Torque Compensation Model and Touchdown Detection Model of t...

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Chinese control and decision Conference, CCDC

作者： Ranjiang Wang Jiangbo Zhao Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665478977

In this paper, according to the different dynamic models of the support phase and the swing phase, the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC). This compensation can increase the tracking effect of the foot end on the swing trajectory, reduce the elasticity and damping coefficient of the virtual model method, and increase the flexibility of the leg. Then this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the leg. At the end of this paper, simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.

关键词： Legged locomotion Damping Torque Switches Hydraulic systems Elasticity Mathematical models

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Parameter-Dependent H2 state Estimation for Nonlinear systems

Parameter-Dependent H2 State Estimation for Nonlinear System...

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第三十四届中国控制会议

作者： Yin Yu Zhen Li Xiangdong Liu Bing Liu School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

The state estimation of general nonlinear systems is investigated through a parameter-dependent approach. This paper adopts the polytopic approximation for the nonlinear systems, which facilitates the application of analytical approaches for resultant convex-bounded linear systems into the given nonlinear systems. The design of a high performance H2 state estimator is firstly determined by solving a convex optimization problem constrained by relaxed linear matrix inequalities(LMIs). The tensor product(TP) model transformation is then adopted to obtain the polytopic linearization. Specifically, A new process is presented to correct the result of the TP model transformation such that a necessary condition to solve the state estimation problem is assured. Finally, a numerical simulation is performed to illustrate the design process and verify the performance.

关键词： Nonlinear state estimation,parameter-dependent H2 filter,linear matrix inequalities(LMIs),tensor product(TP) model transformation

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