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CSAA/IET International Conference on Aircraft Utility Systems (AUS 2020)

作者： J. Wang X. Zhang J. Huang X. Wang G. Xiong T. Wang Beijing Institute of Automatic Control Equipment Beijing 100074 China Beihang University School of Automation Science and Electrical Engineering Beijing 100191 China

In this paper, a modified observer-based reconfigurable fault-tolerant control (FTC) strategy for the aircraft model with multi-actuator closed-loop system faults was presented. The aircraft hybrid states, including the obtained observer states and the remaining normal states, are used to reconfigure the optimal FTC gain under specific fault condition by linear quadratic regulator (LQR) technique. The switching mechanism is designed to realize smooth switching between different control gains. The convergence of the modified observer, and the proposed FTC controller are verified by using numerical simulation finally.

关键词： fault tolerance actuators control system synthesis fault diagnosis closed loop systems observers linear quadratic control

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Patient-Specific Seizure Prediction Using Convolutional Neural Networks and Scalp EEG 12

Patient-Specific Seizure Prediction Using Convolutional Neur...

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12th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2019

作者： Chen, Wei Li, Huiyan Zheng, Hailing Yang, Yaru Yang, Li Qin, Yingmei Han, Chunxiao Tianjin Key Laboratory of Information Sensing Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781728148526

Seizures are key characteristics epilepsy, which can be captured by scalp EEG. An accurate method of predicting seizures will help to alleviate the helplessness and uncertainty of patients. Seizures vary dramatically between patients and even in an individual patient. Here we propose to design a patient-specific seizure prediction model based on convolutional neural networks (CNNs). First, the short-time Fourier transform (STFT) is applied on 30-s EEG windows to extract spatiotemporal information of the preictal and interictal EEG signals. Then the CNN is built based on machine learning algorithms for automatic feature extraction and classification to achieve the prediction of seizures. The area under ROC Curve (AUC) is used to evaluate the performance of CNN models. The mean value of AUC is 0.94, the average false prediction rate (FPR) is 0.09/h, and the sensitivity of more than half of patients is above 95%. © 2019 IEEE.

关键词： Convolution

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Optimizing the teaching efficiency of english classrooms in colleges and universities based on deep learning

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AIP Conference Proceedings 2024年第1期2937卷

作者： Y. Dileep Kumar M. Praveen Kumar A. Mahesh Reddy G. Vamsi Krishna G. V. Sunil Kumar Department of Electronics & Instrumentation Engineering SreeVidyanikethan Engineering College A. Rangampeta Tirupati-517102 India. Department of Control & Automation School of Electrical Engineering VIT University Katpadi Vellore 632014 Tamilnadu India. Department of Electronics &Communication Engineering Sri Venkatesa Perumal College of Engineering & Technology Puttur-517583 India. Department of Electronics & Instrumentation Engineering Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Chikkadapally Hyderabad500020 India. Project Manager Involute Automation (P) Ltd Balanagar Hyderabad-500037 Telangana India

An accurate assessment of the quality of English classroom instruction is essential for moving English education reform forward while also raising English education standards in Chinese colleges. A comparison model for evaluating the quality of English classroom teaching is built using SVM-LM (Support vector machine-Learning Machine) model together with Particle Swarm Optimization (PSO). The SVM-LM approach reduces the need for experiment samples while enhancing model fit because fewer hidden layer neurons are required for accuracy. According to results from experiments, utilizing the SVM- LM algorithm to assess English classroom instruction is a realistic option. Consequently, the study created English classroom teaching effectiveness index system has been successful and is intended to increase the standard of English language classroom instruction as well as how it is administered. The study results proved that the proposed algorithm works better than PSO.

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How to secure distributed filters under sensor attacks

arXiv

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arXiv 2020年

作者： He, Xingkang Ren, Xiaoqiang Sandberg, Henrik Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Affiliated with Digital Futures Sweden Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

—We study how to secure distributed filters for linear time-invariant systems with bounded noise under false-data injection attacks. A malicious attacker is able to arbitrarily manipulate the observations for a time-varying and unknown subset of the sensors. We first propose a recursive distributed filter consisting of two steps at each update. The first step employs a saturation-like scheme, which gives a small gain if the innovation is large corresponding to a potential attack. The second step is a consensus operation of state estimates among neighboring sensors. We prove the estimation error is upper bounded if the filter parameters satisfy a condition. We further analyze the feasibility of the condition and connect it to sparse observability in the centralized case. When the attacked sensor set is known to be time-invariant, the secured filter is modified by adding an online local attack detector. The detector is able to identify the attacked sensors whose observation innovations are larger than the detection thresholds. Also, with more attacked sensors being detected, the thresholds will adaptively adjust to reduce the space of the stealthy attack signals. The resilience of the secured filter with detection is verified by an explicit relationship between the upper bound of the estimation error and the number of detected attacked sensors. Moreover, for the noise-free case, we prove that the state estimate of each sensor asymptotically converges to the system state under certain conditions. Numerical simulations are provided to illustrate the developed results. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

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Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

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A Goal-Biased RRT Path Planning Approach for Autonomous Ground Vehicle

A Goal-Biased RRT Path Planning Approach for Autonomous Grou...

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Conference on Vehicle control and Intelligence (CVCI)

作者： Xianjian Jin Zeyuan Yan Hang Yang Qikang Wang Guodong Yin State Key Laboratory of Automotive Simulation and Control Jilin University Changchun China School of Mechatronic Engineering and Automation Shanghai University Shanghai China School of Mechanical Engineering Southeast University Nanjing China

ISBN: (数字)9781728184975

ISBN: (纸本)9781728184982

For the application of autonomous ground vehicle (AGV) operating in unstructured environment, a path planning method based on an improved goal-biased Rapidly-exploring Random Trees (bias-RRT) is proposed. The algorithm combines random sampling with numerical optimization to achieve fast convergence speed and satisfy constraints. KD-Tree and potential field of the environment are implemented to increase the sampling efficiency, and cubic B-splines are used to smooth the path for better tracking performance. The algorithm improves the efficiency of searching while guarantee safety and quality of the planned path. Simulation results verify the effectiveness of the proposed method.

关键词： Simulation Path planning Land vehicles Safety Splines (mathematics) Optimization Convergence

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Dynamic Characteristics of Ball Bearing-Coupling-Rotor System with Angular Misalignment Fault

Research Square

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Research Square 2021年

作者： Wang, Pengfei Xu, Hongyang Yang, Yang Ma, Hui He, Duo Zhao, Xiang School of Mechanical Engineering and Automation Northeastern University Liaoning Shenyang110819 China China North Vehicle Research Institute Beijing100072 China Key Laboratory of Vibration Control of Aero-Propulsion System Ministry of Education Northeastern University Liaoning Shenyang110819 China

The rotor misalignment fault, which occurs only second to unbalance, easily occurs in the practical rotating machinery system. Rotor misalignment can be further divided into coupling misalignment and bearing misalignment. However, most of the existing references only analyze the effect of coupling misalignment on the dynamic characteristics of the rotor system, and ignore the change of bearing excitation caused by misalignment. Based on the above limitations, a five degrees of freedom nonlinear restoring force mathematical model is proposed, considering misalignment of bearing rings and clearance of cage pockets. The finite element model of the rotor is established based on the Timoshenko beam element theory. The coupling misalignment excitation force and rotor unbalance force are introduced. Finally, the dynamic model of the ball bearing-coupling-rotor system is established. The radial and axial vibration responses of the system under misalignment fault are analyzed by simulation. The results show that the bearing misalignment significantly influences the dynamic characteristics of the system in the low-speed range, so bearing misalignment should not be ignored in modeling. With the increase of rotating speed, rotor unbalance and coupling misalignment have a greater impact. Misalignment causes periodic changes in bearing contact angle, radial clearance, and ball rotational speed. It also leads to reciprocating impact and collision between the ball and cage. In addition, misalignment increases the critical speed and the axial vibration of the system. The results can provide a basis for health monitoring and misalignment fault diagnosis of the rolling bearing-rotor system. © 2021, CC BY.

关键词： Rotating machinery

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Neural Network Tracking of Switched Robotic Manipulators with Mode-Dependent Average Dwell Time

Neural Network Tracking of Switched Robotic Manipulators wit...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Chao Ma Wei Wu Yidao Ji Wei Wang School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper is concerned with the tracking control for robotic manipulators with switching loads and parameter uncertainties. More precisely, the neural network approximation method is adopted with adaptive control to deal with the unmodeled dynamics. Multiple Lyapunov function method is used based on mode-dependent average dwell time, such that the tracking error can converge with desired region. A numerical example is finally provided for illustrating our proposed tracking strategy.

关键词： Switches Robots Manipulators Neural networks control systems Manipulator dynamics Uncertain systems

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Optimal Local and Remote controls of Networked Systems: Multiplicative Noise Case

Optimal Local and Remote Controls of Networked Systems: Mult...

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International Conference on control and automation (ICCA)

作者： Qingyuan Qi Lihua Xie Huanshui Zhang Institute of Complexity Science College of Automation Qingdao University Qingdao China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

In this paper, the linear quadratic (LQ) optimal control problem is studied for multiplicative noise networked control systems (MN-NCSs) with two controllers of different information structures. The challenges and difficulties of the considered problems are twofold: Firstly, the system dynamics is described by a multiplicative noise system and regulated by a local control and a remote control, which may cause separation principle to fail. Besides, by adopting the Pontryagin maximum principle, the local controller can not be solved from the equilibrium conditions directly. To overcome these difficulties, an innovative approach is adapted to solve the forward and backward stochastic difference equations (FBSDEs). It is verified that the separation principle holds, and the optimal local control and optimal remote control are derived based on coupled Riccati equations.

关键词： Uplink Remote control Optimal control Symmetric matrices Additive noise Riccati equations Mathematical model

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nonlocal quark condensate from Dyson-Schwinger Equation and its contributions to the gluon vacuum polarization based on OPE approach

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying Huan, Chen Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China School of Mathematics and Physics China University of Geosiciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

The operator-product expansion(OPE) could be employed to obtain the lowest-order, nonlocal quark scalar condensate component of gluon vacuum polarization. In particular, nonlocal quark scalar condensate can be calculated by solving Dyson-Schwinger Equation(DSE) of QCD. Then, field-theoretic aspects of the gluon vacuum polarization and nonperturbative gluon propagator will be considered in the Landau gauge of the Lorentz gauge fixing. The gluon propagator we obtained is finite in the infrared domain where the single gluon mass mg can be determined. Our results of the ratio mg/ΛQCD the range of that from 1.33 to 1.39 agree with previous determinations for this ratio. Besides, the analytic structure of the gluon propagators from the OPE's result is explored. Our numerical analysis of the gluon' Schwinger function finds clear evidence of the positivity violations in the gluon propagator. In addition, a new method for obtaining the chemical potential dependence of the gluon vacuum polarization and the dressed gluon propagator is developed. © 2021, CC BY.

关键词： Polarization

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