{"id":166,"date":"2020-01-24T10:26:15","date_gmt":"2020-01-24T10:26:15","guid":{"rendered":"http:\/\/128.131.86.19\/?page_id=166"},"modified":"2020-01-24T13:22:25","modified_gmt":"2020-01-24T13:22:25","slug":"mathmod-2015-plenary-lectures","status":"publish","type":"page","link":"https:\/\/www.mathmod.at\/index.php\/previous-mathmods\/mathmod-2015\/mathmod-2015-plenary-lectures\/","title":{"rendered":"MATHMOD 2015 Plenary Lectures"},"content":{"rendered":"\n<p><em>MATHMOD 2015<\/em> featured four plenary lectures:<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>What has Instrumental Variable method to offer for system identification?<\/strong><br> Prof. Marion Gilson-Bagrel<br> Universit\u00e9 de Lorraine, Nancy, France<\/li><li><strong>Model-based approaches for the future sustainable aircraft: the EU ADDSAFE project<\/strong><br>Dr. Philippe Goupil, R&amp;T Engineer<br>AIRBUS &#8211; Flight Control System, Toulouse, France<\/li><li><strong>Advanced Mechatronics for Precision Engineering and Mechatronic Imaging Systems<\/strong><br>Prof. Georg Schitter<br>Vienna University of Technology, Austria<\/li><li><strong>(Dynamic) Iteration Schemes for Coupled Problems in Electrical Engineering<\/strong><br>Prof. Sebastian Sch\u00f6ps<br>TU Darmstadt, Germany <\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Abstracts<\/h2>\n\n\n\n<p><strong>What has Instrumental Variable method to offer for system identification?<\/strong><br><strong>Prof. Marion Gilson-Bagrel<\/strong><br><strong>Universit\u00e9 de Lorraine, Nancy, France<\/strong><\/p>\n\n\n\n<p>For\n many years, several attempts have been made to identify accurate linear\n or non linear plant models, by several algorithms, and with or without \nthe need to identify full noise models.<\/p>\n\n\n\n<p>More precisely, when \nlooking at methods that can consistently identify plant models of \nsystems while relying on simple linear (regression) algorithms, \ninstrumental variable (IV) techniques seem to be rather attractive, but \nat the same time not very often applied.<\/p>\n\n\n\n<p>However, IV methods of \nparameter estimation have a long history in the statistical and control \nengineering literature and present some interesting properties.<\/p>\n\n\n\n<p>On  the other hand, when dealing with highly complex processes that are  high dimensional in terms of inputs and outputs, it can be attractive to  rely on methods that do not require non-convex optimization algorithms.  Besides this computationally attractive property, IV methods have the  potential advantage that they can identify plant models consistently  when the noise model is misspecified, and in the particular case of  closed-loop system identification, when the present controller is  non-linear and\/or time-varying.<\/p>\n\n\n\n<p>The aim of this talk is to give \nsome clues of the use of those IV methods in several kinds of \napplications (linear, LPV, time domain, frequency domain, environmental \ndata set, water quality measurements\u2026) and to illustrate what IV methods\n can offer to system identification.<br><\/p>\n\n\n\n<p><strong>Model-based approaches for the future sustainable aircraft: the EU ADDSAFE project<\/strong><br><strong>Dr. Philippe Goupil, R&amp;T Engineer<\/strong><br><strong>AIRBUS &#8211; Flight Control System, Toulouse, France<\/strong><\/p>\n\n\n\n<p>In\n this presentation a high-fidelity aircraft benchmark, developed by \nAirbus for advanced flight control related studies, is exposed in \nrelation to its evolution towards advanced fault diagnosis within a \nEuropean 7th Framework Program project entitled \u201cAdvanced Fault \nDiagnosis for Sustainable Flight Guidance and Control (ADDSAFE)\u201d. This \nEuropean project was established to study and facilitate the transfer of\n model-based fault detection and diagnosis methods from Academia to \nIndustry. The importance of the project arose on the one hand, due to \nthe representativeness of the benchmark, and on the other hand, the \nindustrial benchmarking and validation of the developed designs. The \nproject had the overall aim of researching and developing model-based \nmethods for detecting and isolating aircraft flight control system \nfaults: predominantly sensor and actuator malfunctions. Most of the \nmodel-based methods rely on the idea of analytical redundancy in which, \nin contrast to physical or hardware redundancy, real physical \nmeasurements are complemented with analytically computed redundant \nvariables. A common method to analytically detect the existence of a \nfailure is to look for anomalies in the plant&#8217;s output relative to a \nmodel-based estimate of that output, generating a so-called residual. \nThe generated residual has to include enough information to determine \nthat a specific fault has occurred.<\/p>\n\n\n\n<p>This presentation provides \ndetails on the ADDSAFE project motivation and objectives. It describes \nthe aircraft model and the fault scenarios defined by Airbus and which \nconstitutes the industrial benchmark. A cursory overview of the \nmodel-based methods studied during the project is proposed. Finally, an \nindustrial perspective is given especially by focusing on the golden \nrules to be followed to help bridge the gap between basic research \nlevels and industrial needs.<\/p>\n\n\n\n<p><strong>Advanced Mechatronics for Precision Engineering and Mechatronic Imaging Systems<\/strong><br><strong>Prof. Georg Schitter<\/strong><br><strong>Vienna University of Technology, Austria <\/strong><\/p>\n\n\n\n<p>Mechatronic\n imaging systems, such as atomic force microscopes (AFM), wafer \nscanners, adaptive optics, and laser scanning microscopes, demand a \ncontinuous improvement of system speed, range, and precision, which \nrequires advanced mechatronic designs and highly sophisticated motion \ncontrol.<\/p>\n\n\n\n<p>Modeling and simulation are key enabling technologies for\n the development and engineering of mechatronic systems in the high-tech\n industry. Already at the system design phase all components involved in\n the specific application have to be considered, where a well \npredictable behaviour of the system components is required. Examples for\n these components are the mechanical structure of the device, the power \namplifier, the actuators, the sensors, electronics, and the real-time \ncontrol system. To meet the demanding specifications, the final system, \nincluding all hard- and software components, has to be tailored to and \noptimized for each specific application.<\/p>\n\n\n\n<p>This presentation \naddresses these challenges by illustrating examples for precision motion\n control, AFM imaging, confocal laser scanning microscopy and adaptive \noptics. The presented examples successfully demonstrate the potential to\n significantly improve the performance of mechatronic imaging systems \nvia an integrated mechatronic design approach by utilizing the interplay\n between process design and control design.<\/p>\n\n\n\n<p><strong>(Dynamic) Iteration Schemes for Coupled Problems in Electrical Engineering<br> Prof. Sebastian Sch\u00f6ps<\/strong><br> <strong>TU Darmstadt, Germany<\/strong><\/p>\n\n\n\n<p>Today,\n due to increased accuracy of modeling and simulation, multi-domain \nproblems become more and more important in many engineering \napplications. Often a monolithic approach, i.e., the solution of all \nsubproblems in one system, is cumbersome or even impossible because \nincompatible algorithms or software packages are involved. Thus \nsimulation engineers need to &#8220;weakly&#8221; couple subproblems in an efficient\n and stable way, such that each problem can be tackled separately. For \nexample for time-dependent problems where different time scales are \npresent, waveform relaxation schemes are a promising approach that \nallows for an efficient simulation of the problem. However, the \nindependent treatment introduces a splitting error, which should be \nmitigated by iterative procedures that in turn can cause computational \noverhead. In this talk we discuss theoretical and practical issues as \nexistence and uniqueness, accuracy, stability and numerical efficiency \nof the schemes and addressed advantages and disadvantages for \nelectromagnetic applications.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>MATHMOD 2015 featured four plenary lectures: What has Instrumental Variable method to offer for system identification? Prof. Marion Gilson-Bagrel Universit\u00e9 de Lorraine, Nancy, France Model-based approaches for the future sustainable aircraft: the EU ADDSAFE projectDr. Philippe Goupil, R&amp;T EngineerAIRBUS &#8211; Flight Control System, Toulouse, France Advanced Mechatronics for Precision Engineering and Mechatronic Imaging SystemsProf. Georg &hellip; <a href=\"https:\/\/www.mathmod.at\/index.php\/previous-mathmods\/mathmod-2015\/mathmod-2015-plenary-lectures\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">MATHMOD 2015 Plenary Lectures<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"parent":146,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"footnotes":""},"class_list":["post-166","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/pages\/166","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/comments?post=166"}],"version-history":[{"count":5,"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/pages\/166\/revisions"}],"predecessor-version":[{"id":629,"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/pages\/166\/revisions\/629"}],"up":[{"embeddable":true,"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/pages\/146"}],"wp:attachment":[{"href":"https:\/\/www.mathmod.at\/index.php\/wp-json\/wp\/v2\/media?parent=166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}