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Data-Driven control of Distributed Event-Triggered Network systems

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 351-364页

作者： Xin Wang Jian Sun Gang Wang Frank Allgower Jie Chen the National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China IEEE the Institute for Systems Theory and Automatic Control University of StuttgartStuttgart 70550Germany the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(*** systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional *** the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is ***,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input ***,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

关键词： Data-driven control distributed event-triggered network system(ETS) linear matrix inequalitie(LMI) looped-functional stability

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Time-Varying Formation control for Multiagent systems with Different Time Delays 9

Time-Varying Formation Control for Multiagent Systems with D...

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9th International Conference on Fuzzy systems and Data Mining, FSDM 2023

作者： Sun, Fenglan Liang, Qinbo Zhu, Wei Li, Qiuying Key Lab of Intelligent Analysis and Decision on Complex Systems School of Science Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781643684703

This article studies the time-varying formation (TVF) problem of multiagent systems (MASs) with different time delays. By designing the control protocol, the followers could achieve the desired TVF. Considering different communication delays, based on graph theory and stability theory, sufficient conditions for the system to realize TVF are obtained. Finally, the numerical example is employed to validate the effectiveness of theoretical results. © 2023 The authors and IOS Press.

关键词： Multi agent systems

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Cross-user Gesture Recognition Based on Deep Domain Adaptation Networks 43

Cross-user Gesture Recognition Based on Deep Domain Adaptati...

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43rd Chinese control Conference, CCC 2024

作者： Fu, Zhongzheng He, Xinrun Wang, Haoyuan Chen, Xingjian Li, Yixuan Huang, Jian Huazhong University of Science and Technology Ministry of Education Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China

ISBN: (纸本)9789887581581

This study introduces an innovative approach for gesture recognition in smart wearable devices using a deep domain adaptation model, focusing on the challenges posed by heterogeneous user environments and the need for precise, adaptable, and personalized gesture recognition systems. Traditional methods based on machine learning and deep learning techniques, while effective, struggle with the variance in data distribution among different users, leading to accuracy challenges. To address this, the study proposes the Domain Kernel-Alignment Adaptation Network (DKAN) model, utilizing a new Kernel-Aligned Multi-kernel Maximum Mean Discrepancy (KAMMD) method within deep networks. By calculating kernel alignments between source and target domains and adjusting weights of Gaussian kernels accordingly, DKAN emphasizes features conducive to transfer learning, enabling more accurate cross-user gesture recognition. The model achieves a significant average accuracy of 97.3% across 21 gestures, highlighting its potential in practical applications. This advancement addresses challenges in traditional gesture recognition methods and sets a new direction for future research in smart wearable technology. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Adversarial machine learning

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CFSeRec:A Contrastive Framework for Sequential Recommendation

CFSeRec:A Contrastive Framework for Sequential Recommendatio...

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第42届中国控制会议

作者： Tong Wang Yaping Dai Shuai Shao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In sequential recommender systems,the main problems are the long-tailed distribution of data and noise interference.A Contrastive Framework for Sequential Recommendation(CFSeRec) is proposed to solve these two problems *** shuffling and adversarial attack data augmentation methods are used in the framework to improve the quality and quantity of training data,so that the long-tailed problem is *** the application of projection head method,the sequence representation becomes more general and robust,rather than just adapted to the task of contrastive ***,the impact of noise on sequence recommender systems is effectively *** on four public datasets show that CFSeRec achieves state-of-the-art performance in the metrics of hit ratio and normalized discounted cumulative gain,when comparing to the seven previous frameworks.

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Deep Co-Training Partial Least Squares Model for Semi-Supervised Industrial Soft Sensing

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3363-3371页

作者： Zheng, Junhua Zhou, Le Ye, Lingjian Ge, Zhiqiang Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Huzhou University Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou313000 China Southeast University School of Mathematics Nanjing210096 China

Data-driven soft sensing has become quite popular in recent years, which can provide real-time estimations of key variables in industrial processes. While the introduction of deep learning does improve the prediction performance, it is highly restricted to the number of labeled training data, as well as large computational burden and cumbersome parameter tuning procedures. How to break through the bottleneck of data-drive models in terms of limited labeled data and high computational complexity should be one of the main recent focuses in the field of industrial soft sensing. In this article, a deep co-training PLS (deep CT-PLS) model is proposed to extend the ordinary PLS model to the semi-supervised deep form. While the deep model can efficiently extract inherent natures of process data, the co-training strategy makes lots of unlabeled data useful through a two-view cross training and annotation process. In this case, the performance restriction of the deep PLS model can be greatly relieved, with the incorporation of additional unlabeled data, while at the same time the designed model structure keeps in a low computational complexity. Based on the case study on a real industrial production process, the deep CT-PLS model can significantly improve the soft sensing performance. © 2013 IEEE.

关键词： Self-supervised learning

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Two Degree of Freedom Active Disturbance Rejection control Strategy for Time Delay systems

Two Degree of Freedom Active Disturbance Rejection Control S...

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第42届中国控制会议

作者： Xiyuan Shan Tao Cai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

This paper is concerned with the controller design and the theoretical analysis for time-delay systems,a two degree of freedom(feedforward and feedback) control method is proposed,which combines advantages of the Smith predictor and the active disturbance rejection control(ADRC).The feedforward part of controller is used to track the set point,the feedback part of controller(ADRC) is used to suppress interferences and the Smith predictor is used to correct time *** proposed control design is easy to tune parameters and has been proved to effectively control systems with large time *** bounded input bounded output(BIBO) stability of closed-loop system is ***,numerical simulations show the effectiveness and practicality of the proposed design.

关键词： Time-delay Active Disturbance Rejection control(ADRC) Smith Predictor(SP)

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Towards Pose Estimation for Large UAV in Close Range 37

Towards Pose Estimation for Large UAV in Close Range

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Ou, Ni Wang, Junzheng Liu, Shangfei Li, Jiehao State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665465366

This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors. © 2022 IEEE.

关键词： Antennas

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Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

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第42届中国控制会议

作者： Tianyi Wang Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

With the aim of 2-AMT electric vehicles,a comprehensive shift schedule that considers both power and economy is ***,the objective function of the comprehensive shift schedule is constructed,which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit ***,Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift ***,AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an *** results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance,and the economy is optimized by 3%.The feasibility of the comprehensive shift schedule is verified.

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Electric dual variable pump controlled hydraulic motor

Electric dual variable pump controlled hydraulic motor

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第42届中国控制会议

作者： Jianmin Yang Junzheng Wang Shanshuai Niu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast ***,due to the inherent nonlinearity of multiplication,it brings certain difficulties to the *** electric double-variable pump[1] is a dual-input single-output system,and it is a nonlinear system[2].It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the *** this paper,an intelligent control rule is proposed for the nonlinear problem of double input and single *** backstepping design[3],the nonlinear system is transformed into multiple linear *** the original system is turned into two independent subsystems with single input and single output,which are controlled *** co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the *** results show that the response speed of the system has been greatly improved.

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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