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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Tang, Wei Feng, Yunjian Li, Jun Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China

ISBN: (纸本)9781665437127

With the rise of deep convolutional neural networks (CNNs), considerable attention has been paid to video anomaly detection (VAD). Autoencoders are a popular type of framework for VAD, and many existing VAD methods are based on it. However, these methods take an assumption of closed-world VAD, i.e., do not comprehensively consider the diversity of normal patterns. Besides, a competent CNN allows the autoencoder to reconstruct or predict abnormal video frames proficiently, resulting in missing anomalies. To mitigate these drawbacks, we propose an Autoencoder with a Memory Module (AMM) to realize video anomaly detection by predicting video frames. AMM consists of three modules: An encoder, a decoder, and a memory module. First, the consecutive frames are fed into the encoder to yield latent spatial features. Then, the features are utilized to retrieve corresponding memory items in the memory module to generate memory mapping features. Finally, the memory mapping features are adopted in the decoder for predicting the next frame. To match the queries against memory items accurately, we propose a memory triplet loss, which takes into account both size and angle discrepancies between the queries and memory items. At the training stage, AMM utilizes the memory triplet loss, a prediction loss, and multi-scale structure similarity measure. Moreover, the modes of retrieving and updating memory items are ameliorated by a scaled dot product model, which can alleviate vanishing gradient problems to a certain extent. Extensive experiments are conducted on three benchmark public datasets, and the results demonstrate the superior performance of AMM. © 2021 IEEE.

关键词： Forecasting

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Secrecy Performance Analysis of RIS Assisted Ambient Backscatter Communication Networks

arXiv

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arXiv 2024年

作者： Pei, Yingjie Yue, Xinwei Huang, Chongwen Lu, Zhiping The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China The Key Laboratory of Information and Communication Systems Ministry of Information Industry China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Hangzhou310027 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Beijing100191 China

Reconfigurable intelligent surface (RIS) and ambient backscatter communication (AmBC) have been envisioned as two promising technologies due to their high transmission reliability as well as energy-efficiency. This paper investigates the secrecy performance of RIS assisted AmBC networks. New closed-form and asymptotic expressions of secrecy outage probability for RIS-AmBC networks are derived by taking into account both imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) cases. On top of these, the secrecy diversity order of legitimate user is obtained in high signal-to-noise ratio region, which equals zero and is proportional to the number of RIS elements for ipSIC and pSIC, respectively. The secrecy throughput and energy efficiency are further surveyed to evaluate the secure effectiveness of RIS-AmBC networks. Numerical results are provided to verify the accuracy of theoretical analyses and manifest that: i) The secrecy outage behavior of RIS-AmBC networks exceeds that of conventional AmBC networks;ii) Due to the mutual interference between direct and backscattering links, the number of RIS elements has an optimal value to minimise the secrecy system outage probability;and iii) Secrecy throughput and energy efficiency are strongly influenced by the reflecting coefficient and eavesdropper’s wiretapping ability. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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MFANet: Mixed Feature Attention Network for Port Lane Detection

MFANet: Mixed Feature Attention Network for Port Lane Detect...

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Chinese control Conference (CCC)

作者： Jinwei Zhang Jinya Su Dewei Yi Jun Yang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education and the School of Automation Southeast University Nanjing China Department of Computing Science University of Aberdeen Aberdeen U.K.

With the advancement of industrial automation and artificial intelligence technology, unmanned port autonomy has gained increasing attention. Port automatic driving technology is a critical component of unmanned autonomous systems, enabling rubber tire gantry cranes (RTGs) to autonomously navigate by detecting port lanes and implementing control commands. In this study, a deep learning-based method is proposed for detecting port lanes in complex port scenes. The method employs the Inception module and attention mechanism to enhance lane feature extraction, and a structural loss is introduced to explicitly constrain the detection results and incorporate the prior characteristics of port lanes. A novel Mixed Feature Attention Network (MFANet) is proposed to implement the method for port lane detection. Experimental results demonstrate that MFANet effectively improves the accuracy of port lane detection while maintaining high computational efficiency. Furthermore, the performance of MFANet is evaluated in a real-world application scenario.

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Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance

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Frontiers of Information Technology & Electronic engineering 2021年第7期22卷 986-1001页

作者： Xuerao WANG Qingling WANG Changyin SUN School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China

In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external *** guarantee the prescribed performance,an error transformation is applied to transfer the time-varying constraints into a constant ***,by employing a barrier Lyapunov function and the backstepping technique,an observer-based tracking control strategy is *** is proven that using the proposed algorithm,all the closedloop signals are bounded,and the tracking errors satisfy the predefined time-varying performance ***,simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme.

关键词： Adaptive tracking control Prescribed performance Input saturation Disturbance observer Neural network

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Finite-Time Observer Based Integral Terminal SMC for Converter-Driven Motor systems with Mismatched Disturbances

Finite-Time Observer Based Integral Terminal SMC for Convert...

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Chinese Automation Congress (CAC)

作者： Zhongding Zhang Zeyu Guo Zuo Wang 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 Shenzhen Research Institute Southeast University Shenzhen China

Converter-driven motor systems play crucial roles in contemporary industrial applications owning to the advantages of smooth starting and stepless speed regulation. For such fourth-order systems with both immeasurable states and mismatched disturbances, a finite-time control solution is proposed to address the speed tracking problem in this paper. Firstly, a finite-time observer is constructed to precisely estimate the immeasurable states and mismatched disturbances. Then, based on integral terminal sliding mode control (ITSMC), a continuous finite-time controller is designed for the systems to achieve both rapid response and superior speed tracking performance. Furthermore, a rigorous global finite-time stability analysis for the closed-loop system is presented. Finally, simulation results validate the effectiveness of the proposed control method. As compared with existing methods, the composite ITSMC algorithm design demonstrates reliable finite-time speed tracking performance and exceptional capability in disturbance rejection.

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Adaptive Load Balancing Routing Algorithm for Low Earth Orbit Satellite Cluster Networks

Adaptive Load Balancing Routing Algorithm for Low Earth Orbi...

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International Conference on Computers, Communications, and systems (ICCCS)

作者： Liming Wang Zhan Xu Ruxin Zhi Jiahui Wang School of Electronics and Communication Engineering Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

Large-scale satellite networks are a crucial component of future communication systems. However, they pose several challenges to satellite routing design and link recovery. This paper proposes an Adaptive Load Balancing routing algorithm for Low Earth Orbit (LEO) Satellite Cluster Networks (ALBSCN) to meet the needs of large-scale Low Earth Orbit LEO satellite networks. The constellation is divided into clusters, with each cluster maintaining the intra-cluster link state by electing a cluster head. The cluster head computes intra-cluster and inter-cluster routes. Messages are forwarded using inter-cluster multipath routing and intra-cluster routing techniques. We validated the algorithm's performance and compared it with other algorithms in terms of packet delivery delay using simulation. Simulation results indicate that the proposed clustering routing scheme effectively reduced packet loss and end-to-end delay, while also increasing network throughput.

关键词： Satellites Adaptive systems Simulation Clustering algorithms Low earth orbit satellites Packet loss Routing

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Intelligent Gear Shifting Strategy of Mining Truck Based on Deep Learning and Real-Time Vehicle Condition

SSRN

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SSRN 2023年

作者： Su, Qinghua Xu, Xiaoyu Wang, Liyong Zhang, Dingge Xie, Min Zhang, Pengbo Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China Laboratory for Visual Perception and Intelligent Systems School of Control Science and Engineering Shandong University Shangdong Province Jinan250100 China

Mining areas are characterized by complex driving conditions, making automatic gear shift strategies specifically suited for mine trucks are critical. Nevertheless, development of automatic gear shifting strategy is under challenging, as it relies on experience and historical experiment data which is the top classified commercial secret of the manufacturers. Recently, some gear shifting strategies have been implemented based on artificial intelligent technology. However, many of them shift the gear based on vehicle current status and ignore the influences of historical data. It has potential risk by making wrong shift when receiving abnormal sensor data accidentally. Besides that, it also causes the gear continuous shifting within short time, which increases the chance of transmission damage and influences the driving experience. Consequently, a novel method based on Bi-directional Long Short-Term Memory(Bi-LSTM) network with multiple parameters from continuous time spans for gear prediction is proposed. The real-time vehicle status data is becaptured from CAN-bus, and 9 types of parameters with positive relation for gear shifting are chosen by R/S analysis. By inputting values of 9 paramters from continuous time spans to our Bi-LSTM based machine learning model, gear prediction target is achieved. The experimental records show that our network outputs the gears best suited to the current vehicle state with 96.85% accuracy. Its average prediction time consumption is around 3.86ms, which fits the real-time processing requirement in driving. Our network not only has advantages in balancing prediction correct rate and time consumption, but also maintains high accuracy when overcoming the influence of transient abnormal sensor data. Hence, it has the potential to be widely applied to the fields that prediction model is based on the data with temporal characteristic. © 2023, The Authors. All rights reserved.

关键词： Long short-term memory

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Finite Time Disturbance Observer-Based Tube Model Predictive control for Vehicle Platoon systems with Guaranteed L∞ String Stability

Finite Time Disturbance Observer-Based Tube Model Predictive...

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Chinese control and Decision Conference, CCDC

作者： Qian Chen Jinhao Liu Jun Yang 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

ISBN: (纸本)9781665478977

This paper investigates optimal longitudinal control problems for a vehicle platoon in presence of parameter uncertainties and external disturbances. First, a multi-constraint multi-objective optimization model is developed, where physical limits, safety constraints, driving comfort, and fuel economy are taken into account. To reduce communication burden and avoid network congestion, the preceding vehicle’s acceleration is obtained by employing a finite time disturbance observer (FTDO). As for the parameter uncertainties as well as external disturbances, they are estimated as a lumped disturbance by exploiting a FTDO. Then, under a predecessor following communication topology, a FTDO-based tube model predictive control method with explicit consideration of string stability is contrived. Finally, numerical simulations illustrate the effectiveness and superiority of the proposed control approach.

关键词： Uncertain systems Network topology Fuel economy Numerical simulation Stability analysis Topology Safety

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Simple Full-Spectrum Correlated k-Distribution Model based on Multilayer Perceptron

arXiv

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arXiv 2024年

作者： Wang, Xin Kuang, Yucheng Wang, Chaojun Di, Hongyuan He, Boshu School of Information and Communication Engineering Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing102206 China Beijing100176 China Institute of Combustion and Thermal Systems School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China

While neural networks have been successfully applied to the full-spectrum k-distribution (FSCK) method at a large range of thermodynamics with k-values predicted by a trained multilayer perceptron (MLP) model, the required a-values still need to be calculated on-the-fly, which theoretically degrades the FSCK method and may lead to errors. On the other hand, too complicated structure of the current MLP model inevitably slows down the calculation efficiency. Therefore, to compensate among accuracy, efficiency and storage, the simple MLP designed based on the nature of FSCK method are developed, i.e., the simple FSCK MLP (SFM) model, from which those correlated k-values and corresponding ka-values can be efficiently obtained. Several test cases have been carried out to compare the developed SFM model and other FSCK tools including look-up tables and traditional FSCK MLP (TFM) model. Results show that the SFM model can achieve excellent accuracy that is even better than look-up tables at a tiny computational cost that is far less than that of TFM model. Considering accuracy, efficiency and portability, the SFM model is not only an excellent tool for the prediction of spectral properties, but also provides a method to reduce the errors due to nonlinear effects. Copyright © 2024, The Authors. All rights reserved.

关键词： Multilayer neural networks

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Modeling of Photovoltaic modules under shading condition and an error evaluation criterion 4

Modeling of Photovoltaic modules under shading condition and...

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2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Lai, GuangZhi Wang, Dong Li, HaoRan Zhao, Yi Ni, WeiChen Wen, JiaHao State Grid e-commerce Co. Ltd Beijing100053 China State Grid Tianjin Electric Power Company Tianjin300392 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

Energy is the focus of recent years. As one of the most representative new energy sources, solar energy has the characteristics of large reserves and no pollution. The main way to use solar energy is photovoltaic (PV) power generation, and the PV module in the PV power generation system is the component that converts solar energy into electric energy. In the actual power generation process, PV modules often receive uneven solar illumination due to the shadow caused by clouds, trees, buildings, etc., resulting in changes in the output characteristics of PV modules and reduced output efficiency. Therefore, modeling of PV modules under shading condition is very important. This paper presents two simple methods for solving the parameters of PV module models, which require few parameters and are easy to obtain. A modeling method of PV modules under shading condition is also presented. And then the modeling method is verified with the experiment result. Finally, an error criterion for PV module modeling under shading condition is proposed to measure the goodness of the modeling. Combining with the two parameter solving methods, the errors of this PV module modeling method under shading condition of the error criterion proposed in this paper are 3.24% and 2.51%, respectively, which meet the requirements for engineering use. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Solar energy

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