{"title":"Convex hull manipulation based control performance optimization: Case study of impedance model with feedback delay","authors":"P. Gróf, P. Galambos, P. Baranyi","doi":"10.1109/SAMI.2012.6209018","DOIUrl":"https://doi.org/10.1109/SAMI.2012.6209018","url":null,"abstract":"Varying delay is still a challenge to handle in the comtrol of systems with feedback delay. This paper attempt to handle varying delay by a novel approach. The control structure has been already proposed, where the system with feedback delay is approximated by a non-delayed model with modified time constants. The controller is designed according to this non-delayed substitute system and the control signal is computed using its observed state vector. Tensor Product (TP) Model Transformation is utilized to make a compact polytopic representation of the observer and controller for various time delays. In this method the actual value of the feedback delay is considered as an input parameter of the TP type controller and observer. In this paper we show that the convex hull of Convex type TP model applied for LMI based controller design has effect on control performance. We introduce a concept how to improve the control performance of the system with feedback delay via convex hull manipulation.","PeriodicalId":158731,"journal":{"name":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121471241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An iterative statistical method for congestion prevention in transit networks","authors":"M. Hrubý, M. Olsovsky, M. Kotocová","doi":"10.1109/SAMI.2012.6208954","DOIUrl":"https://doi.org/10.1109/SAMI.2012.6208954","url":null,"abstract":"With the expanding amount of data transferred over communication links it is necessary to improve the links and appropriate network devices to match the traffic requests. The most common way of increasing network throughput and performance in general is usually the replacement of the network devices and links. This way is reliable but usually expensive. Different way of improving network performance is the change of way how the traffic is handled and distributed over network. In this paper we propose an algorithm for dynamic traffic rerouting in IP networks based on statistical probability and load experienced on a network link. This algorithm accomplishes congestion prevention and even distribution of traffic on available network resources.","PeriodicalId":158731,"journal":{"name":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133700302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juraj Števek, A. Szucs, M. Kvasnica, S. Kozák, M. Fikar
{"title":"Smart technique for identifying hybrid systems","authors":"Juraj Števek, A. Szucs, M. Kvasnica, S. Kozák, M. Fikar","doi":"10.1109/SAMI.2012.6208995","DOIUrl":"https://doi.org/10.1109/SAMI.2012.6208995","url":null,"abstract":"The paper describes a system identification method for a nonlinear system based on a multi-point linear approximation. We show that under mild assumptions, the task can be transformed into a series of one-dimensional approximations, for which we propose an efficient solution method based on solving simple nonlinear programs (NLPs). The approach provides identification of nonlinear systems in a polynomial model structure (ARX, OE, BJ) from input-output data. The approximation is based on a neural network modelling procedure. The proposed modelling procedure is characterized by fast training, adjustable accuracy and reduced complexity of the final model. The modelling technique is widely applicable in automotive, power electronics, computer graphics, etc.","PeriodicalId":158731,"journal":{"name":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}