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Impulsive Containment control for Linear Multi-Agent Systems with Self-Feedback and Aperiodic Sampling 11

Impulsive Containment Control for Linear Multi-Agent Systems...

引用

11th International Conference on Information Science and Technology, ICIST 2021

作者： Chen, Jiejie Chen, Boshan Zeng, Zhigang Jiang, Ping Zhu, Yi Hubei Normal University College of Computer and Information Huangshi435002 China Hubei Normal University College of Mathematics and Statistics Huangshi435002 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan435000 China Hubei PolyTechnic University Computer School Huangshi435002 China

ISBN: (纸本)9781665412667

In this paper we discuss the impulsive containment control problem of continuous-time linear multi-agent systems. Firstly, an impulsive control protocol with self-feedback and aperiodic sampling is proposed, in which the coupling matrix do not have to be Laplacian. Utilizing the proposed protocol, the impulsive containment control problem for continuous-time linear multi-agent systems is equivalently transformed into the stabilization problem of some independent linear discrete-time switched systems. Then a mode-dependent switching-type Lyapunov function is constructed, some sufficient conditions are showed by using some linear matrix inequalities to achieve the containment control purpose. In addition, based on a linear matrix inequality, the controller gain matrix can be designed to solve the containment control problem. In obtained results, the self-feedback gain, the size and the switching frequency of the sampling intervals can play all important roles. Finally, two simulation examples are employed to validate the effectiveness of the theoretical results. © 2021 ieee.

关键词： Multi agent systems

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Remote Sensing Inversion for River Turbidity Estimation Based on Noise Injection and Ensemble Learning

Remote Sensing Inversion for River Turbidity Estimation Base...

引用

2021 China automation Congress, CAC 2021

作者： Zhou, Yazhen Shi, Shuang Liu, Hongyan Zhang, Yonghui Gu, Ke Qiao, Junfei Faculty of Information Technology Beijing University of Technology Beijing 100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute

ISBN: (纸本)9781665426473

Turbidity is one main indicator of quality typically used for monitoring water pollution and water eutrophication. The monitoring technology of river water quality can be divided into contact monitoring technology based on physical sensors and non-contact monitoring technology based on remote sensing satellites. The traditional contact monitoring technology has limited monitoring spatial resolution. As a new technology, the remote sensing monitoring technology of the river can conveniently solve the above-mentioned shortcomings and realize the coverage of the whole river basin. However, due to the scarcity of remote sensing data and the measurement errors of remote sensing satellites themselves, learning-based turbidity measurement methods have weak generalization ability and thus are easily prone to produce large deviations. To effectively address such difficulty, a noise injection method is introduced into a river turbidity measurement model based on ensemble learning. To be specific, we randomly generate many noise sets and add them to the remote sensing data to make it closer to the real application scene, and then adopt the ensemble learning model to estimate river turbidity. Experiments validate that the random noise injection strategy can effectively improve the generalization performance of river turbidity measurement. © 2021 ieee

关键词： Rivers

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Evaluation of air quality variability in Timioara, Romania 14

Evaluation of air quality variability in Timioara, Romania

引用

14th ieee International symposium on Applied computational intelligence and Informatics, SACI 2020

作者： Gruicin, Iasmina Ionascu, Marian-Emanuel Popa, Mircea University Politehnica of Timioara Faculty of Automation and Computers Timioara300223 Romania

ISBN: (纸本)9781728173764

This study presents the evaluation and analysis of air pollution levels in Timioara, Romania, regarding the main air pollutants. We examined diurnal, monthly and seasonal variations, using datasets of measurements from the four existing fixed air quality monitoring stations in Timioara. The results show that the station TM-1, located in the south of the city, has overall much higher values that the other stations. All pollutants except for ozone show peaks in the diurnal variation in the morning and late in the afternoon, which can be correlated to the traffic rush hours, and fall and winter dominance in the seasonal variation. Ozone variation follows the chemistry of its formation, showing proportional increases with the increase of sunlight and ultraviolet radiation. © 2020 ieee.

关键词： Air quality

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Evaluating Image Quality of DIBR-synthesized Views in Texture and Depth Domains

Evaluating Image Quality of DIBR-synthesized Views in Textur...

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2021 China automation Congress, CAC 2021

作者： Wang, Guangcheng Guo, Nan Liu, Hongyan Zhang, Yonghui Zhou, Yazhen Gu, Ke Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China

ISBN: (纸本)9781665426473

Accurately predicting the quality of depth-image-based-rendering (DIBR) synthesized images is of great significance in promoting DIBR techniques. Recently, Many DIBR-synthesized image quality assessment (IQA) algorithms based on quantifying the distortion existed in texture images have been proposed. However, these methods ignore the damage of DIBR algorithms on the depth structure of DIBR-synthesized images and thus fail to evaluate the visual quality of DIBR-synthesized images accurately. To this end, we present a DIBR-synthesized image quality assessment metric with multi-modal information (i.e. integrating texture and depth information), dubbed as MMI. MMI predicts the quality of DIBR-synthesized images by jointly measuring the texture structure and depth structure of the synthesized image. The design principle of our MMI is that the local geometric distortion, introduced by DIBR techniques in the hole-filling process, destroys the texture structure and the depth structure of DIBR-synthesized images. Thus, we can accurately evaluate DIBR-synthesized image quality by a joint representation of texture structure and depth structure. Experiments show that our MMI is better than the competing state-of-the-art IQA algorithms in predicting DIBR-synthesized image quality. © 2021 ieee

关键词： Textures

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Information model for the digital transformation of manufacturing systems in small and medium enterprises

Information model for the digital transformation of manufact...

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ieee International Conference on Automatica (ICA-ACCA)

作者： M William Gutierrez Jesús A. López Jesús Hamilton Ortiz Engineering faculty Universidad Autónoma de Occidente SENNOVA research instructor at the SENA National Learning Service National system of science technology and innovation in Colombia of Colciencias is a professional member and member of the Computational Intelligence Society of the IEEE Taylor and Francis-CRC group

ISBN: (纸本)9781665494090

This article proposes the development of an information model that allows starting the digital transformation of a small or medium-sized company (SME) using the OPC UA protocol. The model is made up of a hardware component made up of the process plant and the control equipment, as well as a software component where the information model is *** an application case, the proposed information model is developed in a unit process plant, a filtration plant. The process carried out in this plant is through a filter to remove the solid particles present in the water used in the manufacturing process of a beverage. This plant can be integrated into a beverage and/or soft drink manufacturing system in a small *** information model is integrated into an OPC UA server, a programmable controller, mapping the process variables such as level, temperature flow, and energy consumption. The information of the technological elements that make up the filtration plant are: serial, manufacturer, and calibration dates: OPC UA clients request information from the OPC UA server and then they are sent through procedures (methods) defined in the server and consumed by the server. client, all this integrates the information *** foregoing shows the viability of the proposed

关键词： Protocols Temperature Filtration Digital transformation Process control Companies Aerospace electronics

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Towards Using Digital Intelligent Assistants to Put Humans in the Loop of Predictive Maintenance Systems 17th

Towards Using Digital Intelligent Assistants to Put Humans i...

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17th IFAC symposium on Information control Problems in Manufacturing (INCOM)

作者： Wellsandt, Stefan Klein, Konstantin Hribernik, Karl Lewandowski, Marco Bousdekis, Alexandros Mentzas, Gregoris Thoben, Klaus-Dieter Univ Bremen BIBA Bremer Inst Prod & Logist GmbH Hochschulring 20 D-28359 Bremen Germany Natl Tech Univ Athens NTUA Inst Commun & Comp Syst ICCS Informat Management Unit IMU 9 Iroon Polytech Str Athens 15780 Greece Univ Bremen Fac Prod Engn Badgasteinerstr 1 D-28359 Bremen Germany

Predictive maintenance systems are socio-technical systems where the interaction between maintenance personnel and the technical system is critical to achieving maintenance goals. Employees who use a predictive maintenance system should explore, modify, and verify their analysis and decision-making methods and rules. Conventional modes of interaction make this difficult since they are often hard to understand, obtrusive and unintuitive. Digital Intelligent Assistants (DIAs) provide fast, intuitive, and potentially hands -free access to systems through voice -based interaction and cognitive assistance. This paper introduces a novel approach to interact with predictive maintenance systems through DIAs. The aim is to integrate human knowledge more effectively into the predictive maintenance process to create a hybrid-intelligence system. In such systems, humans and computers complement and evolve together. Copyright (C) 2021 The Authors.

关键词： Engineering Applications of Artificial intelligence Predictive Maintenance Human-automation Integration Hybrid intelligence Systems

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Models of Two-Wheeled Mobile Robots with Experimental Validation 14

Models of Two-Wheeled Mobile Robots with Experimental Valida...

引用

ieee 14th International symposium on Applied computational intelligence and Informatics (SACI)

作者： Komor, Denis Roman, Raul-Cristian Precup, Radu-Emil David, Radu-Codrut Panfilii, Ion Politehn Univ Timisoara Dept Aut Appl Informat Timisoara Romania Univ Augsburg Dept Control Theory Augsburg Germany

ISBN: (纸本)9781728173764

Two wheeled mobile robots are fully autonomous and self-balancing vehicles. As these systems are nonlinear and open-loop unstable, various and complex control algorithms are needed to guarantee the dynamic system stability. One requirement for the development of a suitable controller is the availability of a reliable mathematical model. This paper treats the mathematical modeling of Two-wheeled Unstable Transporter (UnTrans). The mathematical model of UnTrans is identified using the input/output collected data after a realtime experiment and Grey Wolf Optimizer algorithm.

关键词： Model verification optimization process identification Two-wheeled Unstable Transporter

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VirtualButcher: Coarse-to-fine Annotation Transfer of Cutting Lines on Noisy Point Cloud Reconstruction

VirtualButcher: Coarse-to-fine Annotation Transfer of Cuttin...

引用

International symposium on computational intelligence and Informatics

作者： Raphael Falque Teresa Vidal-Calleja Malcolm McPhee Edwina Toohey Alen Alempijevic Robotics Institute (UTS:RI) at the University of Technology Sydney (UTS) Australia NSW Department of Primary Industries Australia

ISBN: (纸本)9781665426855

Robotics and automation are rapidly becoming part of meat processing operations. Current automation of breaking down a carcass into primals relies on guidance from X-ray, inter-connected with robotised band-saws. While yielding very accurate cutting lines, the use of vision systems for guidance would be significantly more affordable. This work proposes a novel method that solves the annotation transfer between a 3D noise-free cut-ting line annotated on a CT acquired canonical model and a noisy target in the form of a point cloud acquired by RGB-D cameras. The proposed coarse-to-fine method initially aligns the posture of each body using a non-rigid deformation algorithm and then performs a local search to solve the surface correspondence which is later used to morph the template non-rigidly. We quantitatively assess the approach by benchmarking with multiple state-of-the-art algorithms on a public available human pose dataset. We also present a proof of concept evaluation on lamb carcasses.

关键词： Point cloud compression Solid modeling automation Three-dimensional displays Annotations Machine vision Cameras

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Using Generative Adversarial Networks for Detecting Stock Price Manipulation: The Stock Exchange of Thailand Case Study

Using Generative Adversarial Networks for Detecting Stock Pr...

引用

ieee symposium Series on computational intelligence (ieee SSCI)

作者： Leangarun, Teema Tangamchit, Poj Thajchayapong, Suttipong King Mongkuts Univ Technol Thonburi Dept Control Syst & Instrumentat Engn Bangkok Thailand Natl Sci & Technol Dev Agcy Natl Elect & Comp Technol Ctr Pathum Thani Thailand

ISBN: (纸本)9781728125473

We implemented an automated system that uses unsupervised learning to detect stock price manipulation events. Generative adversarial networks (GANs) were trained with regular market transactions in a limit order book format. GANs can recognize normal trading behaviors of good governance stocks with the various price ranges, trading volume, and market capitalization. Stocks that were traded differently were assumed to be suspicious, thus required further manual investigation. We tested the system with 6 real manipulation cases that had been prosecuted from the stock exchange of Thailand. The proposed system can identify 5 out of 6 cases correctly with a very low false-positive rate.

关键词： anomaly detection stock market stock price manipulation detection unsupervised learning

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Comparative Evaluation of Dependability for Voltage and Reactive Power control by Modified Brain Storm Optimization using Individual and Sub-population based Parallel Multi-Population

Comparative Evaluation of Dependability for Voltage and Reac...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Matsumoto, Kaichi Fukuyama, Yoshikazu Meiji Univ Grad Sch Adv Math Sci Tolyo Japan

ISBN: (纸本)9781728125473

Voltage and reactive power control (VRPC) is one of Mixed Integer Nonlinear Programming (MINLP) problems. Evolutionary computation (EC) based VRPC methods have been developed for solving VRPC problems. Since VRPC is an online control, it is necessary to solve a VRPC problem in a limited VRPC interval. Recently, high level of renewable energy penetration and progress of deregulation in power systems require to shorten the VRPC interval and to solve a large-scale VRPC problem in the VRPC interval. Namely, Fast calculation is required in VRPC. Application of parallel and distributed computing (PDC) is a practical option for solving this challenge. However, since power system is a social infrastructure, a dependable method is required for keeping quality of solutions even if several servers cannot return the calculation results due to various faults. When PDC is applied to an EC method using multi-population (MP), there are two ways for realization of parallel computation, namely sub-population based parallel multi-population (PMP) and individual based PMP. No papers have ever compared the two methods from a dependability point of view. This paper presents comparative evaluation of dependability for VRPC by modified brain storm optimization (MBSO) using the individual and the sub-population based PMP. Simulation results with an ieee 118 bus bench mark system indicate higher dependability of the method using the individual based PMP than the method using sub-population based PMP.

关键词： voltage and reactive power control individual based multi-population parallel and distributed computing dependability modified brain storm optimization evolutionary computation

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