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Nonlinear Luenberger observer for velocity estimation in active magnetic levitation system

Nonlinear Luenberger observer for velocity estimation in act...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Rafał Bieszczad Adam Piłat Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Cracow Poland

This article presents the problem of designing a nonlinear observer for an active magnetic suspension system. The design process of the nonlinear Luenberger observer (also known as the Kazantzis-Kravaris-Luenberger observer) is discussed. Particular attention was paid to the main nonlinearity of the system - the electromagnetic force, which was modeled applying the function describing the change in inductance as a function of the distance of the levitating object from the electromagnet surface. Theoretical analyses were confirmed by the results of experimental studies in which the task of moving the sphere between the given positions using current control was carried out. control tasks were conducted in the real-time regime on an embedded platform. The measured signals and estimated velocity were analyzed in the context of future implementations in control applications.

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Intelligent denoising technique for spatial video denoising for real-time applications

Intelligent denoising technique for spatial video denoising ...

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International Conference on computer engineering and Systems

作者： Rasha Orban Mahmoud Mohamed T. Faheem Amany Sarhan Nile Institute of Commerce and Computer Technology Mansoura Egypt Computers and Automatic Control Department Faculty of Engineering Tanta University Egypt

With the wide spread of video usage in many fields of our lives, it becomes very important to develop new techniques for video denoising. Spatial video denoising using wavelet transform has been the focus of the current researches as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered in this work: 2D Discrete Wavelet Transform (2D DWT) and 2D Dual Tree Complex Wavelet Transform (2D DTCWT). Each of these techniques has its advantages and disadvantages. The first technique gives less quality at high levels of noise but consumes less time while the second gives high quality video while consuming long. In this work, we introduce an intelligent denoising system that makes a tradeoff between the quality of the denoised video and the time required for denoising. The system first estimates the noise level in the video frame then accordingly chooses the proper of the two denoising techniques to apply on the frame. The simulation results show that the proposed system is more suitable for real-time applications where the time is critical while giving high quality videos especially at low to moderate levels of noise.

关键词： Noise reduction Gaussian noise Additive white noise Discrete wavelet transforms Video compression Noise level Optoelectronic and photonic sensors AWGN Motion estimation Focusing

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Partitioning methods used in DBS treatments analysis results

Partitioning methods used in DBS treatments analysis results

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International Joint Conference on Neural Networks (IJCNN)

作者： Oana Geman Cornel Turcu Department of Automatic Control and Computers Faculty of Electrical Engineering and Computer Science University Stefan cel Mare of Suceava Suceava Romania

Parkinson's disease is a neurodegenerative disorder and is associated with motor symptoms, including tremor. The DBS (Deep Brain Stimulation) involves electrode implantation into subcortical structures for long-term stimulation at frequencies greater than 100Hz. The mechanism by which chronic, electrical Deep Brain Stimulation with high frequency, suppresses tremor in Parkinson's disease is unknown, but might involve a gradual change in network properties controlling the generation of tremor. First, we performed linear and nonlinear analysis of the tremor signals to determine a set of parameters and rules for recognizing the behavior of the investigated patient and to characterize the typical responses for several forms of DBS. Second, we found patterns for homogeneous group for data reduction. We used Data Mining and Knowledge discovery techniques to reduce the number of data. Then, we found "clusters" the most well-known used and commonly partitioning methods used: K-means and K-medoids. To support such predictions, we develop a model of the tremor, to perform tests determining the DBS reducing the tremor or inducing tolerance and lesion if the stimulation is chronic.

关键词： Satellite broadcasting Clustering algorithms Time series analysis Correlation Algorithm design and analysis Mathematical model Software algorithms

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Predictive maintenance for electrical motors: Current approach and usage of artificial intelligence algorithms

Predictive maintenance for electrical motors: Current approa...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Tomasz Herzog Krzysztof Bartecki Faculty of Electrical Engineering Automatic Control and Computer Science Opole University of Technology Opole Poland Rockwell Automation Power Control Business Katowice Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

The article presents the current approach in artificial intelligence methods used in predictive maintenance for electrical motors. The study focuses on presenting data classification methods for fault detection and isolation using data from condition monitoring systems. We discuss the advantages and disadvantages of using machine learning methods like perceptron and Support Vector Machine (SVM) for fault classification problems. Our conclusion shows great interest in machine learning methods combined with condition monitoring systems. Our future research will focus on comparing SVM, perceptron networks, and other methods, such as K-nearest neighbors, with their possibility for implementation in embedded firmware systems.

关键词： Support vector machines Condition monitoring Accuracy Fault detection Artificial neural networks Machine learning Prediction algorithms

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Virtual instrumentation on mobile devices for measuring the pulse wave velocity

Virtual instrumentation on mobile devices for measuring the ...

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International Conference on Telecommunications and Signal Processing (TSP)

作者： Razvan A. Ciobotariu Criştiăln Fosalau Cristian Rotariu Faculty of Electrical Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Romania

Virtual instrumentation is one of the major development resulted from the extensive use of computers, which offers the benefits of customizable software development of user-defined tools for control, process, and visualization of data, creating versatile systems, using modular programming, intuitive and easy to use. In this paper we present the development and implementation of virtual instrumentation software for medical application running on a mobile device. We choose to develop an application that measures the Pulse Wave Velocity, due to major incidence and impact of cardiovascular diseases.

关键词： Electrocardiography Software Indexes Instruments Mobile handsets Pulse measurements Programming

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Embedding of nonlinear systems in a linear parameter-varying representation 19

Embedding of nonlinear systems in a linear parameter-varying...

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19th IFAC World Congress on International Federation of automatic control, IFAC 2014

作者： Abbas, Hossam S. Tóth, Roland Petreczky, Mihály Meskin, Nader Mohammadpour, Javad Department of Electrical Engineering College of Engineering Qatar University PO Box 2713 Doha Qatar Control Systems Group Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Department of Computer Science and Automatic Control Ecole des Mines de Douai Douai59508 France Intelligent Control Systems Lab. College of Engineering University of Georgia AthensGA30602 United States Electrical Engineering Department Faculty of Engineering Assiut University Assiut Egypt

ISBN: (纸本)9783902823625

This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representations of nonlinear (NL) systems which are originally defined by control affine state-space representations. The conversion approach results in LPV state-space representations in the observable canonical form. Based on the relative degree concept of NL systems, the states of a given NL representation are transformed to new coordinates that provide its normal form. In the SISO case, all nonlinearities of the original system are embedded in one NL function which is factorized to construct the LPV form. An algorithms is proposed for this purpose. The resulting transformation yields an LPV model where the scheduling parameter depends on the derivatives of the inputs and outputs of the system. In addition, if the states of the NL model can be measured or estimated, then the procedure can be modified to provide LPV models scheduled by these states. Examples are included for illustration. © IFAC.

关键词： State space methods

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Multi-person remote heart-rate measurement from human faces - a CNN based approach

Multi-person remote heart-rate measurement from human faces ...

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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Thomas Pursche Marcel Walz Roland Clauß Robert Roth Bernd Tibken Reinhard Möller School of Electrical Information and Media Engineering Automatic Control University of Wuppertal Wuppertal Germany Faculty of Electrical Information and Media Engineering Automatic Control University of Wuppertal Wuppertal Germany Faculty of Electrical Information and Media Engineering Automation/Computer Science University of Wuppertal Wuppertal Germany

The conventional heart rate measurement techniques using electrocardiogram, wrist belts and so on, are attached with some disadvantages like discomfort, irritation of the skin and even more. From this starting point various video based heart rate measurement techniques were developed in the last years. All of these techniques use video data of the human faces to extract information to estimate the heart rate of the person in front of the camera. Most of them work with the detection of minimal changes in the color spectrum of the recorded video data. With these extracted information and multiple concluding steps, they are able to estimate the heart rate of the person sitting in front of the camera. All of these approaches have some big disadvantages, they are only able to measure the heart rate of one person - and in a small number of cases up to three persons. So the main objective of this work is to adapt and enhance existing research approaches of processing visual biological signals. The focus is set on the design and deployment of a new system, which is able to process visual data as well as detect and localize human faces by using artificial neural networks and calculate each individuals heart rate from the processed data's information. For the first time in this research area, different scenarios with more than three observed participants are being analyzed to calculate the heart rate for each of them separately. It will be shown that by using the applied technical architecture and technologies, it is possible to deploy a comparable and qualitatively competitive system. In addition, the implemented system proves the feasibility of processing various faces' signals and calculating the respective heart rates simultaneously within an acceptable range of tolerance.

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LoRA based, low power remote monitoring and control solution for Industry 4.0 factories and facilities

LoRA based, low power remote monitoring and control solution...

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Roedunet International Conference (RoEduNet)

作者： George-Cristian Pătru Dumitru-Cristian Trancă Ciprian-Marian Costea Daniel Rosner Răzvan-Victor Rughiniş Computer Science and Engineering Department University POLITEHNICA of Bucharest Bucharest Romania Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Bucharest Romania

Over the years, industrial automation has repeatedly been impacted by the continuous and tremendous evolution in the fields of computer systems, electronics and data transmission. Industry 4.0, the current wave of the industrial revolution- dubbed the data revolution -, integrates these advances in communication and computational systems with the Internet, resulting in a paradigm shift towards the (Industrial) Internet of Things. Automation systems and remote data acquisition systems evolved over the last years from classic solutions based on wired infrastructure to modern, flexible solutions bringing together wireless communications, battery powered devices and wireless sensors networks. In this paper we first define the main problems encountered in modern wireless automation systems - small distance limitations of wireless communication solutions, weak security or complete lack of security in data transmission, and high energy consumption of battery powered remote data acquisition systems. In order to address these limitations, we propose, implement, trial-run and benchmark a novel low power LoRa-based flexible hardware architecture for use in industrial remote monitoring and control. We obtain a LoS capability above 3km and a calculated autonomy of about 10 years, exceeding the capabilities of current State of the Art solutions.

关键词： Sensors Hardware Batteries Wireless sensor networks Power demand Protocols Industries

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The wireless system for EGG signal acquisition

The wireless system for EGG signal acquisition

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Dariusz Komorowski Stanislaw Pietraszek Damian Grzechca Faculty of Biomedical Engineering Silesian University of Technology Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

The paper provides a case study on the wireless circuit for the purpose of the EGG (Electrogastrography) signal acquisition. The authors present an amplifier based on the ADS1298, wireless communication module (Bluetooth) and the microprocessor unit which have been recently built. The system is currently under examination but the outcome is very promising because the amplifier input is fed with the pure signal, i.e. no high/low pass filter is applied, that is a novelty. The system presented in this paper could be helpful in diagnosis gastric disorders in noninvasive way. It could determine patients with unexplained nausea, vomiting and other dyspeptic symptoms. The unit is under clinical trials tests and preliminary evaluation indicates acceptance by medical staff. Additional advantages are the relatively low cost of manufacture and the possibility of application remotely (pervasive computing).

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Adaptive identification of fuzzy cognitive networks

Adaptive identification of fuzzy cognitive networks

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4th International Symposium on Communications, control, and Signal Processing, ISCCSP-2010

作者： Psillakis, Haris E. Boutalis, Yannis Giotis, Thomas Christodoulou, Manolis A. Department of Electrical Engineering Technological and Educational Institute of Crete Heraklion Greece Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece University of Erlangen-Nurember Department of Automatic Control Germany Department of Electronic and Computer Engineering Technical University of Crete Chania Crete 73100 Greece Faculty of Electronic and Computer Engineering Technical University of Crete Chania Crete 73100 Greece Dipartimento di Automatica et Informatica Politecnico di Torino 10129 Torino Italy

ISBN: (纸本)9781424462858

An adaptive methodology is introduced to identify the weights of a general Fuzzy Cognitive Network (FCN). The proposed scheme consists of two hierarchically structured individual identification tasks that are both implemented on-line. The inner task employs a robust integral of the sign error (RISE) observer to approximate the system's unknown nonlinearity. At the higher level, a nonlinear mapping of the observer's output provides an estimation of the linear parametrization of the FCN weights. Exploiting this fact, a standard gradient-based algorithm is proposed as an outer identification task to estimate the FCN weights under a persistence of excitation condition. Simulation results illustrate the effectiveness of the proposed approach. ©2010 IEEE.

关键词： Fuzzy logic

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