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第41届中国控制会议

作者： Zhipeng Wang Liping He Huawei Liu Jian Lv Jianlong Qiu School of Automation and Electrical Engineering Linyi University Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the load frequency control(LFC) of the photovoltaic(PV) energy storage system is studied,and the uncertainty disturbance of the system and the communication delay between energy storage equipment and traditional units are *** paper introduces white noise into PV power generation to simulate a more realistic PV power generation *** of the disturbance,the state error of the system cannot be accurately estimated,so the state observer is introduced and the state equation of the system is *** further maintain the stability of the system,the controller is designed based on sliding ***,the feasibility of the control strategy is verified by simulation.

关键词： Sliding mode control Time delay Load frequency control

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STGSA:A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 226-238页

作者： Zebing Wei Hongxia Zhao Zhishuai Li Xiaojie Bu Yuanyuan Chen Xiqiao Zhang Yisheng Lv Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the Shandong Key Laboratory of Smart Transportation(Preparation) Shandong Jiao Tong UniversityShanghai 200240China the College of Science China University of PetroleumQingdao 266580China the Department of Transportation Engineering School of Transportation Science and TechnologyHarbin Institute of TechnologyHarbin 150090China IEEE

The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the *** existing frameworks typically utilize separate modules for spatial and temporal correlations ***,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some ***,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between *** overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies ***,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution *** each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting ***,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven ***,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global *** projects the embedding input repeatedly with multiple different ***,the predicted values are generated by stacking several multi-stream *** experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA

关键词： Deep learning graph neural network(GNN) multistream spatial-temporal feature extraction temporal graph traffic prediction

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Bifurcation control and circuit simulation of a fractional-order synthetic gene networks 41

Bifurcation control and circuit simulation of a fractional-o...

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第41届中国控制会议

作者： Feng Liu Feiyue Zhuo Shujiang Sun Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Artificial Intelligence and Automation Department of Mechanical Engineering Boston University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a ring synthetic gene network model described by fractional differential equations,studies the conditions of Hopf bifurcation in the model,and discusses the limit cycle oscillation phenomenon due to the existence of bifurcation,which causes the system to become unstable,and then We propose a method to control the bifurcation behavior in the system,so that the system can be stable over a large *** addition,the dynamic behavior of the fractional-order model is simulated by triggering a genetic oscillator(a single inhibitory gene) composed of a transistor composed of linear and nonlinear electronic *** circuit simulation results well verify the theoretical analysis conclusion,and the circuit simulation model can well demonstrate the biological characteristics of gene regulatory networks.

关键词： Synthetic gene networks fractional-order bifurcation control circuit simulation

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Non-Smooth Speed control of Switched Reluctance Motor Based on Generalized Proportional Integral Observer

Non-Smooth Speed Control of Switched Reluctance Motor Based ...

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Chinese control Conference (CCC)

作者： Qingzhao Yin Zheng Tian Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

This paper investigates the speed regulation control of switched reluctance motor (SRM) systems. To improve the antidisturbance performance of SRM, a composite non-smooth control strategy is proposed. First, the structure of SRM is analyzed, and a simplified nonlinear model is obtained based on a segmented representation of the varying phase inductance. A virtual control function is introduced to represent the nonlinear part of the torque equation, whose inverse function is cascaded to linearized the nonlinear model. Second, a generalized proportional integral observer (GPIO) is constructed to estimate the lumped disturbance of the system, which is used for feedforward compensation design. Finally, a composite speed controller is designed based on a combination of finite time proportional feedback and feed-forward compensation based on GPIO (FTP+GPIO). The speed error closed-loop system can be regarded as a first-order finite time control system with bounded disturbances. Strict analysis shows that the proposed scheme can improve the anti-disturbance performance of the closed-loop system. The effectiveness of the proposed method is verified by simulation results. Moreover, it is compared with proportional feedback combining feed-forward compensation (P+GPIO) method and proportional integral (PI) control method.

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Adaptive control for Stochastic Nonlinear systems with Input Saturation Based on Multi-dimensional Taylor Network

Adaptive Control for Stochastic Nonlinear Systems with Input...

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IEEE International Conference on Mechatronics and automation

作者： Xiao-Yi Zheng Hong-Sen Yan Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Automation Southeast University Nanjing China

For stochastic nonlinear systems with input saturation, few of the existing control methods use a suitable auxiliary system to solve input saturation problem, and most of them are for deterministic systems. In this study, according to the backstepping approach and the Lyapunov stability theorem, utilizing multi-dimensional Taylor network (MTN), an adaptive controller is presented to secure that all closed-loop signals keep bounded in probability, in which MTN is implemented to approach the uncertain function during the controller design. Moreover, the impact raised by input saturation is mitigated by designing an appropriate auxiliary system, in which the order of the auxiliary system is the same as that of the controlled system. Furthermore, unlike the majority of prior findings, the final output signal could be constrained in a mean quartic sense by an explicit expression of the input saturation error (the difference between the control signal and the saturation input) and the parameters used for design. Finally, the efficiency of the suggested control methodology is confirmed by providing an example.

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Dynamic Performance Prediction in Batch-Based Assembly System with Bernoulli Machines and Changeovers

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complex System Modeling and Simulation 2022年第3期2卷 224-237页

作者： Zunjun Wang Zhiyang Jia Xiuxuan Tian Jingchuan Chen Bei Pan State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Industrial and Manufacturing Systems Engineering University of Hong KongHong Kong 999077China School of Engineering Tokyo University of TechnologyTokyo 192-0982Japan

Worldwide competition and diverse demand of customers pose great challenges to manufacturing enterprises. How to organize production to achieve high productivity and low cost becomes their primary task. In the mean time, the rapid pace of technology innovation has contributed to the development of new types of flexible automation. Hence, increasing manufacturing enterprises convert to multi-product and small-batch production, a manufacturing strategy that brings increased output, reduced costs, and quick response to the market. A distinctive feature of small-batch production is that the system operates mainly in the transient states. Transient states may have a significant impact on manufacturing systems. It is therefore necessary to estimate the dynamic performance of systems. As the assembly system is a typical class of production systems, in this paper, we focus on the problem of dynamic performance prediction of the assembly systems that produce small batches of different types of products. And the system is assumed to be characterized with Bernoulli reliability machines, finite buffers, and changeovers. A mathematical model based on Markovian analysis is first derived and then, the analytical formulas for performance evaluation of three-machine assembly systems are given. Moreover, a novel approach based on decomposition and aggregation is proposed to predict dynamic performance of large-scale assembly systems that consist of multiple component lines and additional processing machines located downstream of the assemble machine. The proposed approach is validated to be highly accurate and computationally efficient when compared to Monte Carlo simulation.

关键词： flexible assembly system dynamic performance Bernoulli machines finite buffers changeovers

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Stability Analysis for the Vehicular Platoon System With Time- Varying Delay via A State Decomposition Method

Stability Analysis for the Vehicular Platoon System With Tim...

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automation, control and Robotics engineering (CACRE), International Conference on

作者： Hang Xu Chuan-Ke Zhang Xing-Chen Shangguan Li Jin Yang Li Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences

ISBN: (数字)9798350350302

ISBN: (纸本)9798350350319

In this paper, the consideration of the stability problem for the vehicular platoon system (VPS) with communication delays under proportional differential (PD) control is studied by the Lyapunov- Krasovskii functional (LKF). Firstly, a VPS considering delay is modeled to analyze the influence of delays for the VPS in operation. Then, an error state-space system of the VPS is constructed and transformed into a singular system. As a result, the stability criterion is proposed based on the state decomposition method via the LKF. Finally, the tolerance for delay is calculated for a case of four vehicles with different controller gains. The result shows that the proportional gain is inversely proportional to the time delay and the differential gain is in direct proportion to the time delay meanwhile. Besides, the high-speed vehicular platoon is more affected by the time delay.

关键词： automation Delay effects Roads Stability criteria Estimation Delays PD control

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Efficient Circuit Diagram Retrieval via Graph Representation

Efficient Circuit Diagram Retrieval via Graph Representation

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Chinese automation Congress (CAC)

作者： Ming Gao Hongcai Chen Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex System Ministry of Education School of Automation Southeast University Nanjing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the field of electronic engineering, the retrieval of circuit diagrams has become an area of considerable research interest. This is attributed to the critical role it plays in consulting legacy electronic designs and in the identification of design plagiarism. Existing image retrieval techniques, which are proficient in managing natural images, typically involve the conversion of images into feature vectors and retrieve similar images according to the closeness of these vectors. However, these methods encounter limitations when adapted to the more specialized and complex domain of circuit diagrams. This paper introduces an innovative approach to the retrieval of circuit diagrams through the use of a graph representation of these diagrams. This novel approach effectively transforms the retrieval task into a graph retrieval problem. The methodology proposed in this paper is comprised of two main components: A recognition algorithm for circuit diagrams designed to accurately extract the components and the topological structure of the circuit and a retrieval strategy based on graph similarity. This methodology is pioneering in its use of graph representation for circuit diagram retrieval, incorporating topological features that are often not considered by conventional image retrieval methods. The experimental results presented in this paper validate the effectiveness of the proposed approach.

关键词： Patents Machine learning algorithms Databases Plagiarism Circuit simulation Image retrieval Integrated circuit interconnections Transforms Feature extraction Vectors

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Bayesian Exponential Regularized Tensor Based Approach for Sparse Geomagnetic Data Completion

Bayesian Exponential Regularized Tensor Based Approach for S...

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2023 International Conference on Sensing, measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023

作者： Li, Guoyu Bin, Junchi Liu, Huan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering University of British Columbia OkanaganBCV1V 1V7 Canada

ISBN: (纸本)9798350318012

Geomagnetic data is vital for predicting earthquakes and magnetic storms. In this regard, a new Bayesian exponential regularized tensor completion framework for sparse geomagnetic data, i.e. BERTC, is proposed to address this problem in the study. First, the spatiotemporal geomagnetic data is reshaped into a 3D tensor with days and hours that features random missing elements. Second, a Gibbs sampling algorithm is developed to achieve probabilistic inference on matrices' factors and corresponding parameters in this model. Thus, the sparse tensor can be gradually optimized to fill the missing entries during iterations. Third, an exponential regularizer is proposed to reduce oscillations before and after iterations to enhance imputation quality further. Finally, the derived factor matrices are aggregated from Gibbs sampling to complete the sparse tensor. Numerical geomagnetic datasets from 13 cities are employed, and extensive comparison experiments are conducted to evaluate the imputation performance of the BERTC. The results show the superiority of the proposed BERTC compared to the state-of-the-art methods in terms of imputation accuracy, with an approximate improvement of the imputation accuracy as no less than 20%. © 2023 IEEE.

关键词： Matrix algebra

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A Deep Learning Based Personal Authentication Method Using sEMG Signal 41

A Deep Learning Based Personal Authentication Method Using s...

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第41届中国控制会议

作者： Lina Tong Mingjia Zhang Daisong Liu Hanghang Ma Yuxiang Zhang Liang Peng School of Mechanical Electronic & Information Engineering Chinese University of Mining and Technology-Beijing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChina Academy of Science

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Personal authentication means that the relevant system confirms whether the identity of the user is real,legal and unique.A safe and convenient personal authentication method is a core for guarantee the security of our information and *** Electromyography(sEMG),which exists on the surface of the skin,is a good signal to achieve personal authentication,for it is difficult to be extracted and *** this paper,a new personal authentication method using forearm sEMG is ***,8-channel sEMG signals are recorded by Myo armband that is placed on right forearm of 14 subjects who perform the same hand open ***,two different deep learning models are presented to classify the *** multi-layers Convolution Neural Network(ML-CNN) and two stages Long Short Term Memory(2 s-LSTM) Network can achieve accuracy of 97.50% and 93.60% respectively,shows it is feasible to achieve the goal of personal *** the time cost of ML-CNN is higher than the 2 s-LSTM,both are lower than human reaction *** the architecture of ML-CNN is more suitable to achieving the goal of personal authentication.

关键词： Personal Authentication Surface Electromyography(sEMG) Myo multi-layers Convolution Neural Network(CNN) LSTM Network

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