Pub Date : 1900-01-01DOI: 10.1109/SAMI.2012.6209018
P. Gróf, P. Galambos, P. Baranyi
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.
在具有反馈延迟的系统控制中，变延迟仍然是一个难题。本文尝试用一种新颖的方法来处理变延迟。已经提出了控制结构，其中具有反馈延迟的系统由一个具有修改时间常数的非延迟模型近似。根据该非延迟替代系统设计控制器，并利用其观测状态向量计算控制信号。利用张量积模型变换(Tensor Product Model Transformation, TP)对不同时滞的观测器和控制器进行了紧凑的多边形表示。该方法将反馈延迟的实际值作为TP型控制器和观测器的输入参数。在基于LMI的控制器设计中，我们证明了凸型TP模型的凸壳对控制性能的影响。我们介绍了如何通过凸包操作来改善带有反馈延迟的系统的控制性能。
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Pub Date : 1900-01-01DOI: 10.1109/SAMI.2012.6208954
M. Hrubý, M. Olsovsky, M. Kotocová
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.
{"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}
Pub Date : 1900-01-01DOI: 10.1109/SAMI.2012.6208995
Juraj Števek, A. Szucs, M. Kvasnica, S. Kozák, M. Fikar
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.
{"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}
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