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arXiv 2019年

作者： Heshmati-alamdari, Shahab Nikou, Alexandros Dimarogonas, Dimos V. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

— Motion control of underwater robotic vehicles is a demanding task with great challenges imposed by external disturbances, model uncertainties and constraints of the operating workspace. Thus, robust motion control is still an open issue for the underwater robotics community. In that sense, this paper addresses the tracking control problem of 3D trajectories for underactuated underwater robotic vehicles operating in a constrained workspace including obstacles. In particular, a robust Nonlinear Model Predictive control (NMPC) scheme is presented for the case of underactuated Autonomous Underwater Vehicles (AUVs) (i.e., vehicles actuated only in surge, heave and yaw). The purpose of the controller is to steer the underactuated AUV to a desired trajectory with guaranteed input and state constraints inside a partially known and dynamic environment where the knowledge of the operating workspace is constantly updated on–line via the vehicle’s on–board sensors. In particular, by considering a ball which covers the volume of the system, obstacle avoidance with any of the detected obstacles is guaranteed, despite the model dynamic uncertainties and the presence of external disturbances representing ocean currents and waves. The proposed feedback control law consists of two parts: an online law which is the outcome of a Finite Horizon Optimal control Problem (FHOCP) solved for the nominal dynamics;and a state feedback law which is tuned off-line and guarantees that the real trajectories remain bounded in a hyper-tube centered along the nominal trajectories for all times. Finally, a simulation study verifies the performance and efficiency of the proposed approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Ocean currents

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Application of the Dynamic Iterative Learning control to the Heteroplanar Active Magnetic Bearing

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IFAC-PapersOnLine 2020年第2期53卷 1511-1516页

作者： Lukasz Hladowski Arkadiusz Mystkowski Krzysztof Galkowski Eric Rogers Bing Chu Institute of Control and Computation Engineering University of Zielona Góra ul. Podgórna 50 65-246 Zielona Góra Poland Faculty of Electrical Engineering Bialystok University of Technology ul.Wiejska 45c 15-351 Bialystok Poland School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK

Heteroplanar active magnetic bearings have numerous applications, where one example is a high-temperature gas-cooled reactors. Rotor imbalance, however, may cause problems for critical parts of the system in the form of repetitive periodic vibrations. This is known problem and periodic component extraction is widely used in active magnetic bearing unbalance control laws. More recently, iterative learning control has been considered as an alternative and this paper gives new results on this approach. In particular, a new control law in the 2D systems setting is developed and the results of a simulation based study using the model of a test rig are given, where such a study is an essential step prior to experimental validation.

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Visual SLAM Based on Dynamic Object Removal

Visual SLAM Based on Dynamic Object Removal

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IEEE International Conference on Robotics and Biomimetics

作者： Hanjie Liu Guoliang Liu Guohui Tian Shiqing Xin Ze Ji School of Control Science and Engineering Shandong University Jinan Shandong China School of Computer Science and Technology Shandong University Qingdao Shandong China School of Engineering Cardiff University Cardiff UK

Visual simultaneous localization and mapping (SLAM) is the core of intelligent robot navigation system. Many traditional SLAM algorithms assume that the scene is static. When a dynamic object appears in the environment, the accuracy of visual SLAM can degrade due to the interference of dynamic features of moving objects. This strong hypothesis limits the SLAM applications for service robot or driverless car in the real dynamic environment. In this paper, a dynamic object removal algorithm that combines object recognition and optical flow techniques is proposed in the visual SLAM framework for dynamic scenes. The experimental results show that our new method can detect moving object effectively and improve the SLAM performance compared to the state of the art methods.

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Verification of AA-Diagnosability in Probabilistic Finite Automata is PSPACE-Hard

Verification of AA-Diagnosability in Probabilistic Finite Au...

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IEEE Annual Conference on Decision and control

作者： Christoforos Keroglou Christoforos N. Hadjicostis Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

In this paper we consider the complexity of verifying the property of AA-diagnosability in probabilistic finite automata and establish that AA-diagnosability is, in general, a PSPACE-hard problem. In deterministic and nondeterministic finite automata, the property of diagnosability captures our ability to determine, based on our observation of the activity in a given finite automaton, the occurrence of any fault event, at least if we wait for at most a finite number of events (following the occurrence of the unobservable fault event). In stochastic settings where the underlying system is a probabilistic finite automaton under partial observation, there is not a prevalent notion of diagnosability and many variations have been proposed, including A-diagnosability and AA-diagnosability. Earlier work has shown that the verification of A-diagnosability (also referred to as strong stochastic diagnosability) for a given probabilistic finite automaton is a PSPACE-hard problem. In this paper, we establish that the verification of AA-diagnosability (also referred to as stochastic diagnosability) is a PSPACE-hard problem.

关键词： Automata Hidden Markov models Probabilistic logic Markov processes Complexity theory Fault diagnosis

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A Green Paradigm for Internet of Things: Ambient Backscatter Communications

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China Communications 2019年第7期16卷 109-119页

作者： Wei Zhang Yao Qin Wenjing Zhao Minzheng Jia Qiang Liu Ruisi He Bo Ai Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology and also with Institute of Telecommunication Satellites China Academy of Space Technology (CAST) Beijing Key Lab of Transportation Data Analysis and Mining Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Department of Information Engineering Beijing Polytechnic College Beijing 100042 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

关键词： ambient backscatter (AmBC) RF-powered device Internet of Things (IoT) battery-free tag wire-less sensor

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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Research on Network Traffic Anomaly Detection of Source-Network-Load Industrial control System Based on GRU-OCSVM 3

Research on Network Traffic Anomaly Detection of Source-Netw...

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3rd International Symposium on Resource Exploration and Environmental Science, REES 2019

作者： Huo, Xuesong Wu, Kehe Miao, Weiwei Wang, Liming He, Hui Su, Dawei State Grid Jiangsu Electric Power Co. Ltd. Power Dispatching Control Center Nanjing210000 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Information and Communication Branch of State Grid Jiangsu Electric Power Co. Ltd. Nanjing210019 China

With the large number of distributed generators and diverse loads connected to industrial control systems, there are more and more interactions among power supply, power grid and load. Any network link attack in the source network will affect the security of the industrial control system, resulting in economic loss of the industrial control system. Therefore, it is very important to study the network attacks against the source-network-load industrial control system. Aiming at the current insufficient situation of network traffic anomaly detection in the source-network-load industrial control system, this paper analysed the composition and flow characteristics of the source-network-load system, studied the scheme of network traffic anomaly detection of the source-network-load system, and proposed a network traffic anomaly detection algorithm based on GRU-OCSVM. The time characteristics of the traffic sequence were extracted by the GRU and input into OCSVM for traffic anomaly detection. Finally, the original network traffic of the source-network-load system was collected to construct anomaly detection data set for simulation experiment. The experimental results showed that the proposed method had high detection rate and low false positive rate, which can meet the needs of network traffic anomaly detection in the source-network-load system. © Published under licence by IOP Publishing Ltd.

关键词： Anomaly detection

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Stabilizing Frequency of Microgrid Integrated With Electric Vehicles by Droop control

Stabilizing Frequency of Microgrid Integrated With Electric ...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Mishkat Ullah Jan Ai Xina Shahzad Ali Haseeb Ur Rehmana Sheeraz Iqbala Arsalan Masooda Salman Salmana Muhammad Aurangzeba School of Electrical & Electronics Engineering North China Electric Power University Beijing China School of Computer & Control Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

Emergence of Microgrid (MG) has changed the structure of power system. On one hand, it opened opportunities to integrate renewable energy sources in islanding mode; on the other hand, the power and frequency have become the main hurdles during its islanding operation. In this paper, the droop control technique is used to counter the effect of frequency fluctuation at MG. Wind energy and Photovoltaics are the two renewable energy sources (RES) studied in work. Diesel generator is used to cater the frequency deviations due to intermittent nature of these RES. Microgrid Operator (MGO) is used as a centralized controller to look after all generating units and loads. The MGO sends a reference signal based upon the frequency deviation, which is calculated by the droop controller. This reference signal is sent to all generating units as well Electric Vehicles Operator (EVsO). All the generators and EVsO respond to that reference signal and adjust their generating power accordingly. Electric Vehicles (EV), operated by EVsO, remains in continuous contact with the MGO through communication link. In this work, a centralized approach for the operation of EVsO is employed. There are two main tasks of the EVsO. One is to calculate the cumulative power of all the EVs connected with the MG, by calculating their initial state of charge; and another is, to change the charging and discharging rate of EVs by stratifying the energy needs of both MG and EVs.

关键词： Frequency control Generators Wind turbines Microgrids Electric vehicles Batteries

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Weighted Linear Multiple Kernel Learning for Saliency Detection 2nd

Weighted Linear Multiple Kernel Learning for Saliency Detect...

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2nd EAI International Conference on Robotic Sensor Networks, ROSENET 2018

作者： Zhou, Quan Wu, Jinwen Fan, Yawen Zhang, Suofei Wu, Xiaofu Zheng, Baoyu Jin, Xin Lu, Huimin Latecki, Longin Jan National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Information Engineering China University of Geosciences Wuhan China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China Department of Cyber Security Beijing Electronic Science and Technology Institute Beijing China CETC Big Data Research Institute Co. Ltd. Guizhou Guiyang China Department of Mechanical and Control Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Computer and Information Sciences Temple University PhiladelphiaPA United States

ISBN: (纸本)9783030177621

This paper presents a novel saliency detection method based on weighted linear multiple kernel learning (WLMKL), which is able to adaptively combine different contrast measurements in a supervised manner. Three commonly used bottom-up visual saliency operations are first introduced, including corner-surround contrast (CSC), center-surround contrast (CESC), and global contrast (GC). Then these contrast measures are fed into our WLMKL framework to produce the final saliency map. We show that the assigned weights for each contrast feature maps are always normalized in our WLMKL formulation. In addition, the proposed approach benefits from the advantages of the contribution of each individual contrast operation, and thus produces more robust and accurate saliency maps. The extensive experimental results show the effectiveness of the proposed model, and demonstrate the combination is superior to individual subcomponent. © 2020, Springer Science and Business Media Deutschland GmbH. All rights reserved.

关键词： Center-surround contrast Corner-surround contrast Global contrast Multiple kernel learning Saliency detection

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Review of renewable energy curtailment in China: Current situation and solutions

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AIP Conference Proceedings 2022年第1期2681卷

作者： Yingai Jin Yiwen Zhang Nan Jiang Mingjie Lv Hang Yin Wenyuan Sun Liang Li 1State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130025 China 2College of Automotive Engineering Jilin University Changchun 130025 China 3School of Physics Engineering and Computer Science University of Hertfordshire Hatfield AL10 9AB UK

In recent decades, China's renewable power generation has developed quickly. However, the randomness of output power causes wind and photovoltaic power curtailment. With the rapid development of renewable energy, renewable energy consumption has gradually become the focus of research. This article comprehensively reviews the current situation and practices of reducing the curtailment of renewable energy in China. From the perspective of methods used to stabilize the fluctuation characteristics of generation output, two modes are outlined: based on energy storage devices and complementary wind-solar system. Then, an Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) system simulation model is proposed as a crucial solution to reduce renewable energy waste. Finally, the application and development trend of renewable energy and energy storage technology has prospected.

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