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arXiv 2022年

作者： Zheng, Shiqi Shi, Peng Zhang, Huiyan the School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China the School of Electrical and Electronic Engineering The University of Adelaide AdelaideSA5005 Australia the College of Engineering and Science Victoria University MelbourneVIC8001 Australia the National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective. © 2022, CC BY.

关键词： Multi agent systems

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A fault diagnosis method based on multi-feature fusion and broad learning system

A fault diagnosis method based on multi-feature fusion and b...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Yan Wang Wenkai Hu Weihua Cao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665401166

Reliable fault diagnosis is of practical significance for process safety in modern industrial facilities. This article proposes a data-driven fault diagnosis method based on multi-feature fusion and broad learning. The contributions are twofold: First, a systematic multi-feature extraction approach is presented to extract long-term trend features, short-term trend features, and binary-valued alarm signals; second, a broad learning system based fault diagnosis method is proposed to diagnose faults based on multi-feature fusion and to update the diagnosis model in an incremental manner. The proposed method has a strong nonlinear modeling capability and can also update the diagnosis model incrementally when unseen fault types are detected. The efficacy of the proposed method is demonstrated by simulations with the benchmark Tennessee Eastman (TE) process.

关键词： Fault diagnosis Learning systems Systematics Fault detection Data preprocessing Benchmark testing Feature extraction

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A tuning strategy for microwave filter using variable universe adaptive fuzzy logic system

A tuning strategy for microwave filter using variable univer...

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Chinese Automation Congress (CAC)

作者： Sai Peng Weihua Cao Leyu Bi Yan Yuan Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Microwave filters are the core frequency selection device in 5G base station, which play an important role in the field of communication. The errors of design and processing of microwave filter make it difficult to meet the specific requirements of frequency selection, thus the tuning process before delivery is significant. However, the tuning process relies heavily on skilled workers, resulting in low tuning efficiency and high cost. The automatic tuning method based on fuzzy logic does not depend on the model and has strong applicability. It has great practical value to the production trend of multi-variety, small batch and customization of microwave filters. In this paper, a variable universe adaptive fuzzy tuning method is proposed. First, intelligent optimal contraction-expansion factors based on fuzzy inference are proposed according to expert knowledge. Then, the input universe and output universe are multiplied, and the initial rule is transformed into more effective new rules through the transformation which is adaptive to the variable universe. Last, the effectiveness of the proposed tuning method is verified by simulations.

关键词： Fuzzy logic Adaptation models Adaptive systems Design methodology Production Microwave communication Microwave theory and techniques

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Psychological Resistance Recognition Based on Acoustic Features Extraction

Psychological Resistance Recognition Based on Acoustic Featu...

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Chinese Automation Congress (CAC)

作者： Z. Lv Z. T Liu M. T. Han B. H. Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Psychological resistance can express the change of the client's psychological state, which is considered to be an important factor affecting psychological counseling. This paper proposed a method of psychological resistance recognition based on acoustic features extraction. The method includes three main steps, i.e., statistical acoustic feature extraction, feature selection, and classification. Our method uses statistical acoustic features to express psychological resistance, and analyzes the application value of high correlation features obtained from feature selection in the recognition of different psychological resistance. This method can be used to determine the high correlation features of psychological resistance adaptively, and avoid the deficiency of subjective judgment. A speech database of psychological resistance is built for research needs, in which three psychological consultants and four subjects are involved in psychological counseling with 1200 sentences in speech. The experimental results verified the effectiveness of our method.

关键词： Resistance Employee welfare Correlation Automation Databases Psychology Feature extraction

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Fast control Strategy of Grid-forming Inverter Based on Power Feedforward

Fast Control Strategy of Grid-forming Inverter Based on Powe...

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Chinese control Conference (CCC)

作者： Sheng Zhang Zhijian Fang Qine Liu Muchao Xiang Dingbang Huang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd Xiangyang Power Supply Company Xiangyang China Electric Power Scientific Research Institute of State Grid Hubei Electric Power Co. Ltd Wuhan China

Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid, but its large inertia will affect the dynamic response speed of grid-forming inverter. In order to solve this problem, this paper introduces the loop that affects the dynamic response of grid-forming inverter, and carries out small signal modeling for active loop, analyzes the dynamic performance indicators and determinants of typical second-order system. Thus, a method of adding power feedforward coefficient to the forward channel of the power loop is designed, and the response speed of the system with or without feedforward coefficient under the unit step response is compared. Finally, the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching, then achieves the effect of fast control.

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Electrical activities of neural systems exposed to sinusoidal induced electric field with random phase

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Science China(Technological Sciences) 2019年第7期62卷 1141-1150页

作者： DU Lin CAO ZiLu LEI YouMing DENG ZiChen School of Natural and Applied Science Northwestern Polytechnical University Xi'an 710129 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Xi'an 710129 China School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi 'an 710129 China

The brain neural system is often disturbed by electromagnetic and noise environments, and research on dynamic response of its interaction has received extensive attention. This paper investigates electrical activity of Morris-Lecar neural systems exposed to sinusoidal induced electric field(IEF) with random phase generated by electromagnetic effect. By introducing a membrane depolarization model under the effect of random IEF, transition state of firing patterns, including mixed-mode oscillations(MMOs) with layered inter-spike intervals(ISI) and intermittency with a power law distribution in probability density function of ISI, is obtained in a single neuron. Considering the synergistic effects of frequency and noise, coherence resonance is performed by phase noise of IEF under certain parameter conditions. For the neural network without any internal coupling, we demonstrate that synchronous oscillations can be induced by IEF coupling, and suppression of synchronous spiking is achieved effectively by phase noise of IEF. Results of the study enrich the dynamical response to electromagnetic induction and provide insights into mechanisms of noise affecting information coding and transmission in neural systems.

关键词： induced electric field random phase electrical activity transition coherence resonance synchronous suppression

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Feature Selection and Learning-Based Model for Uav Path Planning on Rough Terrains

SSRN

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SSRN 2022年

作者： Ali, Hub Xiong, Gang Husnain, Haider Muhammad Tamir, Tariku Sinshaw Dong, Xisong Shen, Zhen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Qingdao Academy of Intelligent Industries Qingdao266109 China Chengdu610054 China

Path planning and obstacle avoidance in 3D terrain have been identified as a monumental challenge for a UAV in a variety of autonomous missions, such as disaster management and search and rescue operations. In large terrain areas, it’s a key problem for traditional approaches to search within the point-cloud maps to find a global path for a UAV considering the flight safety, maneuverability, weather constraints, and fuel cost. Hence, this paper proposes a trajectory planning technique for global and local path planning of a fixed-wing UAV above 3D terrain under static and dynamic constraints. For global path generation, a novel Feature Selection and Learning-based Model (FSLM) has been introduced to select the features of a point-cloud map and transform them into the feature set. The feature set is utilized by an improved A* planner with an extensive search area to deliver an optimal global path. The global path is assumed as the UAV's reference waypoints. The motion of the UAV on reference waypoints is simplified with two coordinates (R, d), where R is the cumulative distance covered by the UAV along the reference waypoints and d is its offset distance from the reference line segment in time t. For any local collision, offset trajectories are generated along with reference waypoints to avoid collision. Cost functions have been added so that the best global and local path can be chosen, taking into account altitude, weather, and fuel constraints. The simulation results show the performance of this approach in various complex terrains by considering weather and dynamic constraints, and the results are also compared to other 3D UAV path planning techniques. © 2022, The Authors. All rights reserved.

关键词： Motion planning

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Parallel Building Process Management System

Parallel Building Process Management System

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2021 China Automation Congress, CAC 2021

作者： Liu, Sheng Shen, Zhen Dong, Xisong Hu, Bin Xiong, Gang Chen, Xiaoyu State Key Laboratory for Management and Control of Complex Institute of Automation Chinese Academy of Sciences Beijing China Beijing engineering Research Center of intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426473

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved. © 2021 IEEE

关键词： Engines

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Stealthy False Data Injection Attacks against Extended Kalman Filter Detection in Power Grids

Stealthy False Data Injection Attacks against Extended Kalma...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Yifa Liu Wenchao Xue Shuping He Long Cheng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Key Laboratory of System and Control Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665402460

The power grid is a kind of national critical infrastructure directly affiliated to human daily life. Because of the vital functions and potentially significant losses, the power grid becomes an excellent target for many malicious attacks. Due to the special nonlinear measurements, many detection methods do not match the grid very well. The extended Kalman filter based detection is one of the few methods suitable for nonlinear system detection, and therefore can be used in power system to spot malicious attacks. However, the reliability and effectiveness of the extended Kalman filter based detection have not been fully studied and adequately guaranteed. By proposing a two-step false data injection attack strategy, this paper gives a stealthy way to inject false data of increasing magnitude into the power grid, which can eventually cause a certain degree of deviation of the grid state without being detected. In the simulation, the method proposed in this paper caused a voltage deviation of more than 25% before being discovered in the power system.

关键词： Power measurement Cyber-physical systems Information filters Power grids Safety Power system reliability Kalman filters

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Distributed PV Identification Based on High-Precision Bus Data Analysis

Distributed PV Identification Based on High-Precision Bus Da...

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IEEE International Conference on Networking, Sensing and control

作者： Xincheng Shen Shaoxiong Huang Zhi Li Kaifeng Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Center State Grid Anhui Electric Power Co. Ltd. Hefei China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

With the rapid development of distributed photovoltaic (PV), it is necessary to study its low-cost output identification technology. In this paper, a low-cost PV output identification method is proposed by using feature extraction. This paper analyzes the high-precision bus data, and uses harmonic analysis, wavelet analysis and Ensemble Empirical Mode Decomposition (EEMD) to extract the operating features of PV output. Then this paper screens these extracted features with the correlation between features and PV output, the stability of the features at different times and the difference of features in different signals. The appropriate features are selected for PV output identification, and its identification accuracy is calculated. The experimental results show that with the method of the Ensemble Empirical Mode Decomposition, an appropriate operating feature can be extracted. This feature can identify the distributed PV output in small bus bar when the PV is working stably.

关键词： Photovoltaic systems Empirical mode decomposition Feature extraction Wavelet analysis Stability analysis Sensors Data mining

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