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第35届中国过程控制会议

作者： Xiangyang Qu Zhiwen Wang Pan Zhang Feng Wang College of Electrical and Information Engineering Lanzhou University of Technology Gansu Key Laboratory Advanced Control for Industrial Processes

This paper studies the H∞ sliding mode control(SMC) problem for a class of networked control system(NCS) with hybrid event-triggered scheme and deception attacks. To alleviate the communication burden, a hybrid event-triggered mechanism that combines the time-triggered mechanism(TTM) and event-triggered mechanism(ETM) via a Bernoulli random variable is presented. Then, taking into account the influence of deception attacks on system performance, an observer-based output feedback H∞ SMC method is proposed. By using the linear matrix inequality technique and Lyapunov stability theory, the system is asymptotically stable and with given H∞ performance. In addition, an observer-based SMC law is designed to ensure that the system state trajectory reaches a predefined sliding region. Finally, a numerical simulation is used to verify the effectiveness of the proposed method.

关键词： Networked control system sliding mode control hybrid-triggered mechanism deception attacks

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A hierarchical battery pack balancing method based on capacitance and inductance series connection

A hierarchical battery pack balancing method based on capaci...

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第35届中国过程控制会议

作者： Zheming Yan Aimin An Zhe Guan Zhipeng Luo College of Electrical and Information Engineering Lanzhou University of Technology Key Laboratory of Gansu Advanced Control for Industrial Processes

Aiming at the problem of battery inconsistency in the series use of lithium battery packs, and considering that the non-adjacent battery packs in the battery equalization circuit are restricted by the equalization circuit, a new equalization topology based on the layered equalization circuit in series of capacitors and inductors is proposed. The balance circuit as a whole uses a double-layer balance topology, the bottom circuit uses CUK chopper circuit, the top circuit combined with the high precision of inductive energy storage balance and the fast balance of capacitive energy storage balance, the use of inductance capacitor series balance circuit. The experimental results show that the equalization speed is improved, the equalization time is shortened, and the expected equalization effect is achieved.

关键词： equalization capacitance equilibrium battery packs control strategy

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InterRep: A Visual Interaction Representation for Robotic Grasping

InterRep: A Visual Interaction Representation for Robotic Gr...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yu Cui Qi Ye Qingtao Liu Anjun Chen Gaofeng Li Jiming Chen College of Control Science and Engineering Zhejiang University Hangzhou China College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University and the Key Key Lab of CS&AUS of Zhejiang Province

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Recently, pre-trained vision models have gained significant attention in motor control, showcasing impressive performance across diverse robotic learning tasks. While previous works predominantly concentrate on the significance of the pre-training phase, the equally important task of extracting more effective representations based on existing pre-trained visual models remains unexplored. To better leverage the representation capabilities of pre-trained models for robotic grasping, we propose InterRep, a novel interaction representation method that possesses not only the strengths of pre-trained models, known for their robustness in noisy environments and their proficiency in recognizing essential features, but also the capacity of capturing dynamic interaction details and local geometric features during the grasping process. Based on the novel representation, we introduce a deep reinforcement learning method to learn generalizable grasping policies. The experimental results demonstrate that our proposed representation outperforms the baselines in terms of both training speed and generalization. For the generalized grasping tasks with dexterous robotic hands, our method boasts a success rate nearly 20% higher than methods using the global features of the entire image from pre-trained models. In addition, our proposed representation method demonstrates promising performance when applied to a different robotic hand and task. It also exhibits excellent performance on real robots with a success rate of 70%.

关键词： Training Visualization Motor drives Shape Grasping Feature extraction Robustness

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Construction and application of a novel WGAN-CNN-based predicting approach for dust concentration at underground coal mine working faces

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Environmental Science and Pollution Research 2024年第27期31卷 39271-39284页

作者： Zhou, Banghao Qin, Botao Zhou, Qun Sun, Daowei Chen, Pengpeng Yang, Kai Pan, Qingyan Li, Huizhen Key Laboratory of Gas and Fire Control for Coal Mines China University of Mining and Technology Ministry of Education Jiangsu Xuzhou221116 China School of Safety Engineering China University of Mining and Technology Jiangsu Xuzhou221116 China School of Computer Science & amp Technology China University of Mining and Technology Jiangsu Xuzhou221116 China

To enhance the real-time monitoring and early-warning capabilities for dust disasters in underground coal mine, this paper presents a novel WGAN-CNN-based prediction approach to predict the dust concentration at underground coal mine working faces. Dust concentration, wind speed, temperature, and methane concentration were collected as the original data due to their nonlinear relationship. The consistency between the generated and original data distributions was verified through PCA dimensionality reduction analysis. The predictive performance of this approach was assessed using five metrics (R2, EVS, MSE, RMSE, and MAE) and compared with three other algorithms (Random Forest Regressor, MLP Regressor, and LinearSVR). The findings indicate that a majority of the generated data falls within the distribution range of the real dataset, exhibiting reduced levels of volatility and dispersion. The R2 values of prediction results are all above 98%, and the MSE values are between 0.0007 and 0.0106. The proposed approach exhibits superior predictive accuracy and robust model generalization capabilities compared to alternative algorithms, thereby enhancing the real-time monitoring and early-warning level of dust disasters in underground coal mine. This will facilitate the realization of advanced prevention and control measures for dust disasters, showcasing a wide range of potential applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Disasters

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Optimization Scheduling of Multi-Energy Microgrid Based on the QUBO Quantum Computing Model 19th

Optimization Scheduling of Multi-Energy Microgrid Based on t...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

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Optimal denial-of-service attack scheduling for remote state estimation via sequential observations 43

Optimal denial-of-service attack scheduling for remote state...

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43rd Chinese control Conference, CCC 2024

作者： Yang, Xinxin Ni, Yuqing Chen, Xiaomeng Chen, Shan Liu, Fei Jiangnan University The Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Wuxi214122 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9789887581581

This study investigates the optimal allocation problem of attack energy in multi-system remote state estimation for Cyber-Physical Systems (CPSs). We consider a scenario where there are M independent systems, each equipped with a remote sensor monitoring system. The local estimates from these systems are sent to a remote estimator through a packet loss channel. The objective of the attacker is to degrade the communication channel between the sensors and the remote estimator. Due to capacity limitations, the attacker is restricted to attacking at most one out of M channels. We incorporate interference from other sensors or interference sources into the communication model based on the SINR (Signal-to-Interference-plus-Noise Ratio) model. It should be noted that the same attack power can lead to different packet loss rates in different network environments. From the attacker's perspective, the goal is to find the optimal attack strategy that maximizes the average estimation error of the remote estimator. Given the uncertainties of wireless network environments, we employ the sequentially-observed Markov decision process (SOMDP) framework to solve the problem. By observing the wireless channels, we gather additional information and incorporate it into the decision-making policy, resulting in better performance than using a standard Markov decision process (MDP). The simulation results support our theoretical findings. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Markov processes

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MODEL PREDICTIVE control OF DISCRETE-TIME LINEAR SYSTEMS BY ADMM WITH APPLICATIONS TO TURBOFAN ENGINE control PROBLEMS

Journal of Applied and Numerical Optimization

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Journal of Applied and Numerical Optimization 2023年第2期5卷 201-217页

作者： Teng, Jiao Du, Xian Wang, Lei Wang, Xinwei Wu, Junmei Department of Applied Mathematics The Hong Kong Polytechnic University Hong Kong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China School of Mathematical Sciences Dalian University of Technology Dalian China Department of Engineering Mechanics State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian China

In this paper, we consider optimal control problems with linear discrete state space model, which originate from a class of turbofan engines. The optimization problem associated with each moving horizon estimation (MHE) in classical model predictive control (MPC) is a quadratic programming (QP) problem, and the general QP algorithms does not exploit the structural features of the turbofan engine itself to improve the computational efficiency of the algorithm. In the framework of model predictive control, the turbofan engine model makes the rolling optimization subproblem exhibit a sparse structure. Based on this feature, the alternating direction method of multipliers (ADMM) is employed to solve each optimization sub-problem and design an improved MPC-ADMM algorithm for solving this class of optimal control problems. The simulation results are compared with the MPC-QP algorithm by numerical examples to show the effectiveness and superiority of the novel algorithm. © 2023 Journal of Applied and Numerical Optimization.

关键词： Model predictive control

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A photovoltaic hydrogen generation system using fuzzy logic control-based maximum power point tracking

A photovoltaic hydrogen generation system using fuzzy logic ...

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第35届中国过程控制会议

作者： SongYu Luo AiMin An Yan Wu XianGui Li JiangTao Li College of Electrical and Information Engineering Lanzhou University of Technology Key Laboratory of Gansu Advanced Control for Industrial Processes

In this paper, the modeling of the PV hydrogen production system and the optimization control method are studied, and a compound maximum power point tracking control technique is proposed to improve the quality of PV power generation as well as the efficiency of hydrogen production. Firstly, the overall structure of the PV hydrogen production system is constructed, and mathematical models of PV arrays, PEM electrolyzer, hydrogen storage tanks, storage batteries, etc. are established;secondly,the basic concepts, basic principles, and flow charts of the fuzzy logic control(FLC) and the adaptive Gray Wolf algorithm(GWO) are introduced;finally, the GWO algorithm is combined with the PV hydrogen production system, and maximum power point tracking control control based on this algorithm is modeled and simulation analysis, and the effectiveness and feasibility of the proposed technique are verified by simulation comparison. The simulation results show that the maximum power point tracking control control system based on the adaptive GWO algorithm has a smaller power oscillation range and power loss near the maximum power point, and the dynamic response time of the maximum power point tracking control control system proposed in this paper is shortened by an average of 0.04 s. The power oscillation of the system has been effectively reduced by17.2%, and the energy conversion efficiency has been improved, which highlights the advantages of the scheme. By comparing and analyzing with the traditional maximum power point tracking control optimization control method, it is verified that the proposed method improves the operation index of the PV hydrogen production system to a certain extent, and at the same time reduces the fluctuation amplitude of the input power of the PEM electrolyzer, and strengthens the dynamic balance capability of the PV hydrogen production system.

关键词： Photovoltaic power generation Hydrogen production from electrolyzed water Optimize control

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Unsupervised learning on particle image velocimetry with embedded cross‐correlation and divergence‐free constraint

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IET Cyber-Systems and Robotics 2022年第3期4卷 200-211页

作者： Yiwei Chong Jiaming Liang Tehuan Chen Chao Xu Changchun Pan College of Control Science and Engineering Zhejiang UniversityHangzhouZhejiangChina School of Mechanical Engineering and Mechanics Ningbo UniversityNingboZhejiangChina Ningbo Artificial Intelligence Institute Shanghai Jiao Tong UniversityNingboZhejiangChina The State Key Laboratory of Industrial Control Technology Institute of Cyber‐Systems and ControlZhejiang UniversityHangzhouZhejiangChina School of Electronic Information and Electrical Engineering Key Laboratory of Shanghai Navigation and Location Based ServicesShanghai Jiao Tong UniversityShanghaiZhejiangChina

Particle image velocimetry(PIV)is an essential method in experimental fluid *** recent years,the development of deep learning‐based methods has inspired new ap-proaches to tackle the PIV problem,which considerably improves the accuracy of ***,the supervised learning of PIV is driven by large volumes of data with ground truth ***,the authors consider unsupervised PIV *** has been some work on unsupervised PIV,but they are not nearly as effective as supervised learning *** authors try to improve the effectiveness and accuracy of unsupervised PIV by adding classical PIV methods and physical *** this paper,the authors propose an unsupervised PIV method combined with the cross‐correlation method and divergence‐free constraint,which obtains better performance than other unsupervised PIV *** authors compare some classical PIV methods and some deep learning methods,such as LiteFlowNet,LiteFlowNet‐en,and UnLiteFlowNet with the authors’model on the synthetic ***,the authors contrast the results of LiteFlowNet,UnLiteFlowNet and the authors’model on experimental particle *** a result,the authors’model shows comparable performance with classical PIV methods as well as supervised PIV methods and outperforms the previous unsupervised PIV method in most flow cases.

关键词： neural network particle image velocimetry unsupervised learning

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Joint Self-Paced Learning and Concept Factorization for Multi-view Clustering

Joint Self-Paced Learning and Concept Factorization for Mult...

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第43届中国控制会议

作者： Xuemin Hu Dan Xiong Li Chai School of Information Science and Engineering Wuhan University of Science and Technology State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Concept factorization-based multi-view clustering methods have received much attention and achieved promising ***,they are limited by uncertain noise in the *** improve the robustness of concept factorization-based multi-view clustering methods,a self-paced learning strategy that considers the potential relationship between the distribution of samples and the training order of samples is *** this paper,we propose a joint self-paced learning and concept factorization(SPLCF) method for multi-view *** is,during the training process,self-paced learning can identify the noise data and adaptively assign different weights to different sample *** addition,to preserve the local manifold structure,the graph regularization term is used to effectively constrain the structural features on the data manifold.l2,12-norm is applied to the association matrix,which aims to retain discriminative features and further alleviate the effect of noise in the ***,an iterative algorithm is presented to solve the optimization *** numerical experiments on four benchmark datasets have demonstrated that the proposed algorithm outperforms other state-of-the-art algorithms.

关键词： Self-paced learning Concept factorization Sparsity constraint Multi-view clustering

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