211 research outputs found

    Structural modeling for control design (articulated multibody component representation)

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    High gain, high frequency flexible responses in gimbaled multibody systems are discussed. Their origin and physical significance are described in terms of detailed mass and stiffness modeling at actuator/sensor interfaces. Guyan Reduction, Generalized Dynamic Reduction, inadequate mass modeling detail, as well as system mode truncation, are shown to suppress the high gain high frequency response and thereby lose system flexibility important for stability and performance predictions. Model validation by modal survey testing is shown to risk similar loss of accuracy. Difficulties caused by high frequency responses in component mode simulations, such as DISCOS, and also linearized system mode simulations, are described, and approaches for handling these difficulties are discussed

    Learning for Advanced Motion Control

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    Iterative Learning Control (ILC) can achieve perfect tracking performance for mechatronic systems. The aim of this paper is to present an ILC design tutorial for industrial mechatronic systems. First, a preliminary analysis reveals the potential performance improvement of ILC prior to its actual implementation. Second, a frequency domain approach is presented, where fast learning is achieved through noncausal model inversion, and safe and robust learning is achieved by employing a contraction mapping theorem in conjunction with nonparametric frequency response functions. The approach is demonstrated on a desktop printer. Finally, a detailed analysis of industrial motion systems leads to several shortcomings that obstruct the widespread implementation of ILC algorithms. An overview of recently developed algorithms, including extensions using machine learning algorithms, is outlined that are aimed to facilitate broad industrial deployment.Comment: 8 pages, 15 figures, IEEE 16th International Workshop on Advanced Motion Control, 202

    Enterprise Mashups: A New Approach for Business Solutions

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    A mashup is a Web application that integrates content from different providers in order to create a new service which is not offered by the content provider. The development of this kind of applications involves activities such as accessing heterogeneous sources, combining data from different data sources and building graphical interfaces. This factor limits non-experienced computer users to develop these applications. However, nowadays there are enterpriseoriented tools that allow non-experienced user for building mashups in order to respond business needs in an easy and rapid way. Due to this, the enterprise mashup approach has been widely adopted by a large number of enterprises. This paper presents an overview of the enterprise mashup approach, as well as a review of four enterprise-oriented tools which provide a set of features that allows non-expertise users developing mashups into an enterprise. Finally, we present the challenges to be addressed by enterprise-oriented mashup tools in order to provide an easier and faster way of developing mashups
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