55 research outputs found

    A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method

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    In this paper, thepyvrft, a Python package for the data-driven control method known as Virtual Reference Feedback Tuning (VRFT), is presented. Virtual Reference Feedback Tuning is a control designtechnique that does not use a mathematical model from the process to be controlled. Instead, it uses input and output data from an experiment to compute the controller’s parameters, aiming to minimizean H2 Model Reference criterion. The package implements an unbiased estimate of the controller for MIMO (Multiple-Input Multiple-Output) processes using both least-squares and instrumental variabletechniques. The package also provides accessory functions to import data and to perform MIMO systems simulations, together with some examples

    Data-driven load disturbance rejection

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    Data-driven direct methods are still growing in popularity almost three decades after they were introduced. These methods use data collected from the process to identify optimal controller's parameters with little knowledge about the process itself. However, most of those works focus on the problem of reference tracking, whereas many of the problems faced in real-life are of disturbance rejection or attenuation. Also, the vastly majority of those works identify the parameters of linearly parametrized controllers, which amounts to fixing the poles of the controller's transfer function. Although the identification of the controller's poles is not prohibitive, as hinted by some of the papers, there is little effort on presenting a data-driven solution capable of doing so. With all that in mind, this work proposes a data-driven approach which is able to identify the zeros and the poles of a linear controller aiming at disturbance rejection. Two different one-step ahead predictors are proposed, one that is linear on the parameters and another that is non-linear. Also, two different techniques are employed to estimate the controller parameters, the first one minimizes the quadratic norm of the prediction error while the second one minimizes the correlation between the prediction error and an external signal. Simulations show the effectiveness of the proposed methods to estimate the optimal controller parameters of restricted order controllers aiming at disturbance rejection

    A Neural Network Strategy Applied in Autonomous Mobile Localization

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    In this article, a new approach to the problem of indoor navigation based on ultrasonic sensors is presented, where artificial neural networks (ANN) are used to estimate the position and orientation of a mobile robot.
This approach proposes the use of three Radial Basis Function (RBF) Networks, where environment maps from an ultrasonic sensor and maps synthetically generated are used to estimate the robot localization.
The mobile robot is mainly characterized by its real time
operation based on the Matlab/Simulink environment, where the
whole necessary tasks for an autonomous navigation are done in a hierarchical and easy reprogramming way. 
Finally, practical results of real time navigation related to robot localization in a known indoor environment are shown

    The Forward Physics Facility at the High-Luminosity LHC

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    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

    Transition, Integration and Convergence. The Case of Romania

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    Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

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    无线传感器网络,作为全球未来十大技术之一,集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术,可实时感知、采集、处理、传输网络分布区域内的各种信息数据,在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议,并针对大规模的无线传感器网络设计了一种树状路由协议,它根据节点地址信息来形成路由,从而简化了复杂繁冗的路由表查找和维护,节省了不必要的开销,提高了路由效率,实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR(AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位:工学硕士院系专业:信息科学与技术学院通信工程系_通信与信息系统学号:2332007115216

    Search for single production of vector-like quarks decaying into Wb in pp collisions at s=8\sqrt{s} = 8 TeV with the ATLAS detector

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    Measurement of the charge asymmetry in top-quark pair production in the lepton-plus-jets final state in pp collision data at s=8TeV\sqrt{s}=8\,\mathrm TeV{} with the ATLAS detector

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