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第41届中国控制会议

作者： You Wu Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper investigates the problem of finite-time H state estimation for discrete time-delayed genetic regulatory networks（GRNs） with observations of two hidden-Markov modes.A new GRN model with two Markov jump delays is proposed,of which the mode observations are governed by two hidden-Markov *** sufficient conditions are derived,which guarantee the finite-time boundedness of the estimation error dynamics with prescribed H disturbance attenuation *** state estimator parameters are designed by solving several matrix inequalities.A numerical example is given to illustrate the validity of our results.

关键词： Genetic regulatory networks finite-time H_∞ state estimation hidden Markov model Markov jump delays

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A Soft Grasping Device with the Modularization and Bi-directional Bending Properties 41

A Soft Grasping Device with the Modularization and Bi-direct...

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第41届中国控制会议

作者： Ling-Jie Gai Jie Huang Xiaofeng Zong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work proposes a fully soft grasping device to perform complex tasks,which consists of the modularized soft grippers and the bi-directional bending soft *** the modularized soft gripper part,we adopt caps to seal both ends of the gripper and connect the adjacent knuckles by *** modularized design not only makes the soft grippers like human fingers to achieve segmental bending,but also reduces the waste caused by local *** the soft holder part,we present a bidirectional bending method to automatically adjust the grasping space,and we also establish a mathematical model to describle the relationship between the soft holder's bending angle and the air ***,in order to evaluate the dynamic response and position accuracy of the grasping device,a PID controller is designed for the soft grasping device to track the step,sine,and square wave ***,the great grasping performance of the fully soft grasping device is verified by experiments.

关键词： Modularized soft gripper Soft holder Adjust grasping range automatically PID controller

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Stability Analysis for Delayed Neural Networks via a Relaxed Negative-Determination Quadratic Function Method 41

Stability Analysis for Delayed Neural Networks via a Relaxed...

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第41届中国控制会议

作者： Yu-Long Fan Ke-You Xie Xing-Chen Shangguan Hongzhang Wang Chuan-Ke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents an improved stability condition for neural networks with a time-varying ***,an improved Lyapunov-Krasovskii functional(LKF) is constructed by introducing the delay-product term and the augmented ***,a less conservative delay-dependent stability criterion for neural networks with a time-varying delay is established by utilizing the generalized reciprocally convex combination and a relaxed quadratic function ***,a numerical example is used to illustrate the merit and effectiveness of the proposed stability criterion.

关键词： Neural Networks Time-varying Delay Stability Analysis Reciprocally Convex Matrix Inequality NegativeDetermination Method

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An Improved Exponential Stability Criterion of Generalized Neural Networks With Intermittent Large-Delay Periods 41

An Improved Exponential Stability Criterion of Generalized N...

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第41届中国控制会议

作者： Jin-Meng Xu Yong He Wen-Hu Chen Zhe-Li Yuan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper focuses on the exponential stability analysis of generalized neural networks(GNNs) with time-varying delays,where the time delays include several intermittent large-delay periods(LDPs).First,the improved piecewise augmented Lyapunov-Krasovskii functional(LKF) candidate is constructed based on the delay-dependent state ***,some advanced inequalities are adopted to estimate the derivative of LKF *** with switching techniques,an exponential stability criterion with less conservativeness is *** last,a numerical example is used to verify the advantage of the proposed criterion.

关键词： Time-varying delay Switched delay system Large-delay period Exponential stability

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Adaptive Sliding Mode control for Flexible Dual-manipulator with Friction Compensation

Adaptive Sliding Mode Control for Flexible Dual-manipulator ...

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2022 Chinese Automation Congress, CAC 2022

作者： Song, Tao Zheng, Shiqi Sun, Jiachun Li, Liangguang Chang, Qing Li, Zhipeng China University of Geosciences Wuhan Campus School of Automation China Hubei Key Laboratory of Advanced Control and Intelligent Automation Fo Complex Systems Wuhan China

ISBN: (纸本)9781665465335

This paper focuses on the coordinated tracking control scheme of dual-manipulator based on friction compensation. First, a new dual-manipulator model with flexible joints and friction is constructed;Second, a new adaptive neural control method is proposed for the dual-manipulators with flexible joints. Neural networks are used to approximate the unknown nonlinear dynamics in the model;Third, new state observers are constructed to estimate the joint friction. Based on the observers, the friction can be well compensated. The stability of the system is derived by using Lyapunov method. The simulation results verify the effectiveness of the practical method. © 2022 IEEE.

关键词： Lyapunov methods

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Short-term Load Forecasting with Transformer Based on Fusion CNN-BiGRU

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2025年第5期52卷 1344-1364页

作者： Xie, Tao Xiao, Zhongchuang He, Xiaojun Fan, Yinchun Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Jiaotong University's School of Electromechanical and Vehicle Engineering Chongqing400065 China SINOPEC Sales Co Ltd's Chongqing EJI branch Chongqing400065 China

To improve the accuracy of short-term power load forecasting, a short-term power load forecasting method based on Transformer with fused CNN-BiGRU is proposed. First, the best input data sequence is selected using the Partial Autocorrelation Function (PACF). Next, the importance scores and rankings of the feature data are obtained through the gradient boosting tree algorithm of CatBoost, and the optimal input features are selected. Then, the feature data and load data are combined. Finally, the combined data is used as input for the Transformer fused with CNN-BiGRU. In model training and forecasting, a hybrid forecasting strategy is employed, incorporating elements of multi-step forecasting into single-step forecasting. For the data of each moment, personalized and independent model training is performed, along with forecasting that include hybrid elements. The model replaces the original word embedding and position encoding components of Transformer. It uses CNN-BiGRU to extract high-dimensional feature representations of latent feature information and relative positional information from the input data. The proposed model demonstrates higher forecasting accuracy through validation on two different datasets and comparison with other forecasting models. Additionally, two ablation experiments are conducted. Through systematic ablation experiments, we demonstrate that modifications to the Transformer input layer significantly improve model performance in time series tasks. These results validate the rationality and effectiveness of the proposed approach. The ablation experiments on the method of PACF selecting the optimal input data sequence and CatBoost filtering the optimal input feature data, as well as the hybrid forecasting strategy, further verify the effectiveness and rationality of the data selection methods and forecasting strategies used in this study for short-term power load forecasting. Moreover, to eliminate the zigzagging jitter phenomenon in the foreca

关键词： CatBoost hybrid forecasting strategy PACF Transformer fuses CNN-BiGRU

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Hybrid Group Consensus of Multi-agent systems with Time-delays and Additive Noises 41

Hybrid Group Consensus of Multi-agent Systems with Time-dela...

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第41届中国控制会议

作者： Chuanjian Li Xiaofeng Zong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The hybrid group consensus of multi-agent systems that consist of two groups in environments with time-delays and additive noises is studied in this *** hybrid group consensus implies that the agents in one group achieve strong consensus and the agents in another group achieve weak consensus.A new type of control protocol is proposed to achieve the following hybrid group consensus behavior:the agents in the first group and in the second group achieve strong consensus and weak consensus,*** sufficient conditions are obtained for the hybrid group consensus problem in both mean square and almost sure ***,a simulation example is given to illustrate the feasibility of the theoretical results.

关键词： multi-agent system hybrid group consensus time-delays additive noises

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Rethinking Iterative Stereo Matching from Diffusion Bridge Model Perspective

arXiv

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arXiv 2024年

作者： Shi, Yuguang The School of Automation Southeast University The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

Recently, iteration-based stereo matching has shown great potential. However, these models optimize the disparity map using RNN variants. The discrete optimization process poses a challenge of information loss, which restricts the level of detail that can be expressed in the generated disparity map. In order to address these issues, we propose a novel training approach that incorporates diffusion models into the iterative optimization process. We designed a Time-based Gated Recurrent Unit (T-GRU) to correlate temporal and disparity outputs. Unlike standard recurrent units, we employ Agent Attention to generate more expressive features. We also designed an attention-based context network to capture a large amount of contextual information. Experiments on several public benchmarks show that we have achieved competitive stereo matching performance. Our model ranks first in the Scene Flow dataset, achieving over a 7% improvement compared to competing methods, and requires only 8 iterations to achieve state-of-the-art results. Copyright © 2024, The Authors. All rights reserved.

关键词： optimization

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Real-Time Multi-View Human Pose Estimation System

Real-Time Multi-View Human Pose Estimation System

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

作者： Yuan Yang Yangang Wang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

We present a highly synchronized multi-view hardware acquisition system that simultaneously enables real-time multi-person pose estimation. We design a hardware synchronizer to achieve multi camera synchronous shooting, with a synchronization latency rate of only 10 −8 seconds. Based on this, we construct a multi-view hardware synchronous acquisition system. This system can be flexibly deployed in various environments to capture moving targets, such as bodies, clothing, hands, etc. Leveraging the distributed computing capabilities of the system, we further develop a multi-view multi-person pose estimation algorithm framework that fulfills real-time requirements and achieves an average frame rate of 40FPS in experimental settings while demonstrating robustness against human motion and occlusion.

关键词： Pose estimation Data acquisition Clothing Cameras Hardware Real-time systems Robustness

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Multimodal Multilevel Attention for Semi-Supervised Skeleton-Based Gesture Recognition

SSRN

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SSRN 2024年

作者： Liu, Jinting Gan, Ming-Gang He, Yuxuan Guo, Jia Hu, Kang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

Although skeleton-based gesture recognition based on supervised learning has made promising achievements, the reliance on large amounts of annotation for training poses a significant cost. This paper addresses semi-supervised gesture recognition, aiming to learn feature representations effectively from unlabeled data. To resolve this problem, we propose a novel multimodal multilevel attention network to achieve semi-supervised learning. This model uses an attention mechanism to polymerize multimodal and multilevel complementary semantic information of the hand skeleton, designing a multimodal multilevel contrastive loss to measure the similarity of features for semi-supervised learning. Specifically, our method explores the relationships between joint, bone, and motion to learn more discriminative feature representations. Considering the hierarchy of the hand skeleton, the skeleton data is divided into multilevel (i.e., hand-level, finger-level, and joint-level) to capture complementary semantic information. Furthermore, a multimodal contrastive loss measure similarity among multilevel representations. The proposed method outperforms the semi-supervised skeleton-based gesture recognition tasks, according to extensive experimentation on two challenging datasets from SHREC-17 and DHG 14/28 datasets. © 2024, The Authors. All rights reserved.

关键词： Gesture recognition

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