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Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

Computer Modeling in Engineering & Sciences 2023年第1期134卷 221-239页

作者： Tianyuan Jia Xiangyong Chen Xiurong Yao Feng Zhao Jianlong Qiu School of Automation and Electrical Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of ShandongLinyi UniversityLinyi276005China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and School of AutomationChina University of GeosciencesWuhan430074China

Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.

关键词： Memristor-based neural networks fixed-time synchronization mixed delays discontinuous activations adaptive control

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Research on Temperature Error Calibration Method of Fluxgate Sensor 11th

Research on Temperature Error Calibration Method of Fluxga...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Yang, Ruiping Ge, Jian Luo, Wang Hu, Xiangyun She, Jinhua Chugo, Daisuke Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering Kwansai Gakuin University Osaka669-1330 Japan School of Geophysics and Geomatics China University of Geosciences Wuhan430074 China Hubei Subsurface Multi-scale Imaging Key Laboratory Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9789819647521

The fluxgate sensor is the most widely used sensor in vector magnetic measurement. However, during long-term continuous observation, the fluxgate sensor will produce large measurement errors due to changes in ambient temperature. This paper proposes a temperature calibration method for the fluxgate sensor based on polynomial fitting to address the temperature error of fluxgate sensors. First, the effect of temperature on the performance indicators of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature calibration model of the fluxgate sensor was constructed. And compared it with other temperature calibration method, the result shows that the proposed temperature calibration method is relatively simple and can better achieve real-time calibration for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were implemented. The temperature drift was reduced from about 700 nT before calibration to about 1 nT, root mean square error RMSE=11.7189, indicating that the proposed method has a good temperature calibration effect on the data measured by the fluxgate sensor within the variable temperature background. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Curve Fitting Fluxgate Sensor Temperature Calibration

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Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive control

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 723-733页

作者： Xiongbo Wan Chaoling Zhang Fan Wei Chuan-Ke Zhang Min Wu IEEE the School of Automation China University of Geosciencesthe Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systemsand the Engineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationWuhan 430074China

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic *** addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI *** the designed controller,the involved fuzzy system is ensured to be asymptotically *** examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

关键词： Dynamic event-triggered mechanism(DETM) hybrid dynamic variables model predictive control(MPC) robust positive invariant(RPI)set T-S fuzzy systems

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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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Development of electric cart for improving walking ability — application of control theory to assistive technology

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Science China(Information Sciences) 2017年第12期60卷 262-270页

作者： Jinhua SHE Yasuhiro OHYAMA Min WU Hiroshi HASHIMOTO School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology

This paper explains the development of an electric cart that helps the elderly maintain or improve their physical strength. Unlike commercially available ones, it has a pedal unit that provides some exercise for a user in training his lower limbs. An impedance model describes the feeling of pushing the pedals. The largest pedal load is determined based on a pedaling experiment. An H∞ controller is designed for each of the largest pedal load and virtually no load. A control law, which is based on the concept of dynamic parallel distributed compensation, is designed using the rating of perceived exertion of a driver as a criterion to choose a pedal load between the largest and almost zero. Five university students and twelve elderly people participated experiments to verify the system design and the validity of the system.

关键词： aging Borg’s scale dynamic parallel distributed compensation electrical cart H_∞ control Karvonen formula lower limbs pedaling rating of perceived exertion

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A CUDA-Based Parallel Adaptive Dynamic Programming Algorithm 36

A CUDA-Based Parallel Adaptive Dynamic Programming Algorithm

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第36届中国控制会议

作者： Lu Li Xin Chen Wei Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Adaptive Dynamic Programming（ADP） with critic-actor architecture is a useful way to achieve online learning *** algorithm Gaussian-Kernel Adaptive Dynamic Programming（GK-ADP） that has been developed before has a kind of two-phase iteration,which not only approximates value function,but also optimizes hyper-parameters ***,just like most iteration algorithms are applied in practice,the scale of sample set will increase as the complexity of the system increases,and it will induce a high computation *** order to speed up computation,a practical acceleration method using parallel computation for GK-ADP is presented in this *** realize parallel computation,a high efficient configuration based on CUDA is designed,in which a group of GPUs work in parallel to compute the most complex part of *** comparison test illustrates that the computation burden which hinders GK-ADP’s application is reduced to a large extent when the parallel computing is introduced.

关键词： Gaussian-Kernel Adaptive Dynamic Programming CUDA Parallel Computing GPU

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Short-term Wind Power Prediction by Using Empirical Mode Decomposition Based GA-SVR 36

Short-term Wind Power Prediction by Using Empirical Mode Dec...

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第36届中国控制会议

作者： Hua Xie Min Ding Luefeng Chen Jianqi An Zhangbing Chen Min Wu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Accurate short-term wind power prediction can improve the trade and the dispatch level of wind *** predict the short-term wind power,we investigated the empirical mode decomposition（EMD） of numerical weather prediction（NWP） and genetic algorithm（GA） optimization of support vector regression（SVR）.First,the wind speed data from NWP is decomposed into the EMD components,including multiple intrinsic mode functions（IMFs） and one ***,a genetic algorithmsupport vector regression model（GA-SVR） is used to build models of all ***,the prediction results of all components are integrated,which as input of wind-power curve for obtain the predicted value of wind *** order to validate the proposed method,one real-world dataset was used for model training and testing,and the results show that the proposed method is more accurate and effective than SVR and back propagation neural networks（BPNN）.

关键词： Wind Power Prediction Empirical Mode Decomposition Support Vector Regression Genetic Algorithm Fast fourier Transform Wavelet Filter

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Performance Diagnosis of controller Based on Eigenvector Subspace K-mean Clustering 36

Performance Diagnosis of Controller Based on Eigenvector Sub...

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第36届中国控制会议

作者： Man Hao Wei-Hua Cao Min Wu Yan Yuan Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

To diagnose the specific reasons that lead to deterioration of controller performance and improve the diagnostic accuracy,a performance diagnosis method based on eigenvector subspace K-mean clustering is ***,the number of standard deterioration performance subspace with different degrees of deterioration information is increased on the basis of the eigenvector subspace distance diagnosis method,in which multiple distance values between eigenvector subspaces are ***,K-mean clustering is used to divide these distance values into two classes,and the clustering center with a maximum number of points is selected as the representative ***,current performance degradation factor is attributed to the category that represented by the nearest standard performance *** simulation,a double-tank model is established,and simulation result shows that average accuracy of controller performance diagnosis reaches 99.4%approximately.

关键词： controller performance performance diagnosis eigenvector subspace K-mean clustering

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LRDE:Long-Range Dependency and Salient Feature Enhancement for Co-SOD 41

LRDE:Long-Range Dependency and Salient Feature Enhancement f...

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第41届中国控制会议

作者： LongSheng Wei SiYuan Guo GuanYu Zong Jiu Huang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Different from other salient object detection(SOD) for the task of extracting salient obj ects in a image,collaborative saliency object detection(Co-SOD) targets a set of related image groups,and uses algorithms to find and locate the common collaborative salient objects in related image *** current SOD has achieved remarkable results,but most of the previous researches focus on how to obtain the consistency between images,while the contextual semantic information of images and the features of salient objects are less *** solve these problems,we propose a novel network to capture long-range dependencies on images and enhance(LRDE) the representation of salient ***,In LRDE,we capture the longrange dependencies by the Non-local module to obtain contextual semantic ***,in order to highlight the features of salient objects and enhance the representation of salient objects,we propose the Coordinate Attention module,which embeds the location-attention channel attention and encodes the feature maps as orientation-aware and position-aware attention maps,and It is applied complementary to the input feature map,thereby enhancing the representation of salient *** show that the method outperforms twelve improved methods on four publicly available datasets.

关键词： Co-SOD Long-Range Dependency Feature Enhancement Non-local Module Coordinate Attention Module

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Speaker-independent Speech Emotion Recognition Based on Random forest Feature Selection Algorithm 36

Speaker-independent Speech Emotion Recognition Based on Rand...

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第36届中国控制会议

作者： Wei-Hua Cao Jian-Ping Xu Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Feature selection is a crucial step in the development of a system for identifying emotions in *** to select high correlation features is an open *** paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion *** feature selection of speakerindependent speech based on Random forest is proposed,which can remove the redundant features that have high correlations with each *** on the speech emotion recognition based on Support Vector Machines(SVM) is performed,where the speaker-independent features selected by the proposal and Spearman correlation analysis are used for emotion recognition,*** results show that the proposal achieves 78.6%recognition rate on average,which is 2.2%higher than using Spearman.

关键词： Emotion Recognition Speech Speaker-independent Feature Selection Random forest

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