Event-triggered discrete-time sliding mode control for high-order systems via reduced-order model approach. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 53 (2020), 2, S. 6207-6212
We propose the design of event-triggered (ET) discrete-time sliding mode (DTSM) control for a high-order discrete-time system via a reduced-order model-based approach. This design includes a triggering mechanism using a reduced-order state vector and a controller based on the modified Bartoszewicz' reaching law for a reduced-order model of the system, to stabilize the uncertain high-order system. The main advantages of using a reduced-order vector in the event condition are the low-order synthesis of the controller and the sampling pattern, which may be sparser than the full vector-based design. This motivation arises from the fact that relaxing a few components of the state vector in the triggering mechanism may decrease its rate of violation. An added advantage of the proposal is that the transmission of the reduced-order vector, particularly in a network-based implementation, can outperform the full-order based design due to the severe challenges that exist in the data network. The robust performance for the closed-loop system is achieved using the DTSM control. We show that our proposal guarantees the stability of the full-order plant with the reduced-order triggering mechanism. The control execution is Zeno-free because of the inherent discrete nature of the control. The efficiency of the proposed method is shown using the simulation results of a numerical example.
https://doi.org/10.1016/j.ifacol.2020.12.1716
Sensor fault detection for salient PMSM based on parity-space residual generation and robust exact differentiation. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 53 (2020), 2, S. 86-91
An online model-based fault detection and isolation method for salient permanent magnet synchronous motors is proposed using the parity-space approach. Given the polynomial model equations, Buchberger's algorithm is used to eliminate the unknown variables (e.g. states, unmeasured inputs) resulting in analytic redundancy relations for residual generation. Furthermore, in order to obtain the derivatives of measured signals needed by such a residual generator, robust exact differentiators are used. The fault detection and isolation method is demonstrated using simulation of various fault scenarios for a speed controlled salient motor showing the effectiveness of the presented approach.
https://doi.org/10.1016/j.ifacol.2020.12.099
Data quality assessment for system identification in the age of big data and Industry 4.0. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 53 (2020), 2, S. 104-113
As the amount of data stored from industrial processes increases with the demands of Industry 4.0, there is an increasing interest in finding uses for the stored data. However, before the data can be used its quality must be determined and appropriate regions extracted. Initially, such testing was done manually using graphs or basic rules, such as the value of a variable. With large data sets, such an approach will not work, since the amount of data to tested and the number of potential rules is too large. Therefore, there is a need for automated segmentation of the data set into different components. Such an approach has recently been proposed and tested using various types of industrial data. Although the industrial results are promising, there still remain many unanswered questions including how to handle a priori knowledge, over- or undersegmentation of the data set, and setting the appropriate thresholds for a given application. Solving these problems will provide a robust and reliable method for determining the data quality of a given data set.
https://doi.org/10.1016/j.ifacol.2020.12.103
Parameter preference for the continuous super-twisting-like algorithm based on H∞ norm analysis. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 53 (2020), 2, S. 5141-5146
Im Titel ist "∞" tiefgestellt
In variable structured systems, plenty of designs are built to be homogeneous. Such unperturbed homogeneous dynamics with negative homogeneous degree guarantee finite time convergence. Previous studies provide lower bounds for parameters that result in such finite-time convergence property. In this paper, we propose a new perspective on parameter preference, based on H∞ norm analysis. Contrary to other studies, which propose such norm non-homogeneous or homogeneous, yet of non-zero degree, we build a homogeneous H∞ norm of homogeneous degree zero, thus global and constant. Based on data collected of this norm on the continuous super-twisting-like algorithm, we give recommendations for choosing the parameters.
https://doi.org/10.1016/j.ifacol.2020.12.1157
Methoden des Soft Computing zur Regelung und Diagnose von Magnetlagern. - Ilmenau : Universitätsbibliothek, 2020. - 1 Online-Ressource (267 Seiten)
Technische Universität Ilmenau, Dissertation 2020
Es besteht weltweit eine ausgeprägte Tendenz, durch Einsatz der aktiv geregelten Magnetlagerung die mechanische Reibung und Verschleiß zu vermeiden sowie die einstellbare Systemsteifigkeit und -dämpfung zu ermöglichen. Solche Systeme werden bis anhin über fixed-control-design oder lineare Strategie geregelt, verwenden also Frequenzfilter mit kleinem Wirkungsgrad, begrenzter Cutoff-Frequenz und Zuverlässigkeit im konventionellen Regelkonzept. Der industrielle Einsatz der aktiven Magnetlager in Verbindung mit dem technologischen Prozess insbesondere unter Belast-, Störfall und Einfluss vom starken Rauschen stellt heute hohe Aufforderung an die Stabilität der Positionierung, Funktionszuverlässigkeit und Laufruhe. Diese führen gegenüber konventionelles Regelkonzept zu einer wesentlichen Erneuerung des Regelkonzeptes. So werden die stabile Magnetlagerung bzw. Steuerbarkeit der dynamischen Eigenschaft bis hin zur technischen Grenze ermöglicht. In dieser Arbeit wird ein neuartiges Regelkonzept mithilfe Soft Computing erarbeitet und am Testanlage FLP 500 am Institut für Prozesstechnik, Prozessautomatisierung und Messtechnik der Hochschule Zittau / Görlitz umgesetzt. Dazu bietet sich vor allem die Integration von Soft Computing in der Regelung-, Filterung- und Online-Identifikationstechnik in das System an. Es werden das Führungsverhalten, Störverhalten, der Umdrehungsversuch bzw. Identifikationsversuch angestellt. Der Identifikationsversuch präsentiert die Ergebnisse aus Online-Identifikation mit ausreichender Schnelligkeit und Robustheit gegen Prozessrauschen. Die weiteren Versuchsergebnisse zeigen, dass die Stabilität der Positionierung mit einem variierenden Arbeitspunkt bzw. die Laufruhe, besonderes unter Bedingung vom starken Prozessrauschen, unter Einfluss von der elektronischen bzw. mechanischen Eigenschwingung, vom Messrauschen und von der Messstörung in Sensorik, deutlich optimiert sind. Durch die Adaptionsmöglichkeit ist die Magnetlagerung zudem wesentlich weniger anfällig für die Variation der Arbeitspunkte. Der Vorteil der Zustandsbeobachtung wird durch Anwendung des Kalman-Filters ausgenutzt. Auf diese Weise ist die nahezu vollständige Eliminierung der Störung und Signalverfälschung in Messsignale möglich. Im realen Versuchsstand durchgeführte Untersuchungen belegen die praktische Anwendbarkeit des Konzeptes.
https://nbn-resolving.org/urn:nbn:de:gbv:ilm1-2020000389
IDA-PBC for underactuated mechanical system in implicit representation. - In: 54. Regelungstechnisches Kolloquium in Boppard, (2020), insges. 2 S.
https://edocs.tib.eu/files/e01fn21/1747792950.pdf
BVNet: a 3D end-to-end model based on point cloud. - In: Advances in visual computing, (2020), S. 422-435
Point cloud LiDAR data are increasingly used for detecting road situations for autonomous driving. The most important issues here are the detection accuracy and the processing time. In this study, we propose a new model which can improve the detection performance based on point cloud. A well-known difficulty in processing 3D point cloud is that the point data are unordered. To address this problem, we define 3D point cloud features in the grid cells of the birds view according to the distribution of the points. In particular, we introduce the average and standard deviation of the heights as well as a distance-related density of the points as new features inside a cell. The resulting feature map is fed into a conventional neural network to obtain the outcomes, thus realizing an end-to-end real-time detection framework, called BVNet (Birds-View-Net). The proposed model is tested on the KITTI benchmark suit and the results show considerable improvement for the detection accuracy compared with the models without the newly introduced features.
https://doi.org/10.1007/978-3-030-64556-4_33
Approach for the generation and evaluation of OOP-tasks during online training as well as paper based tests. - In: INTED 2020, (2020), S. 5488-5494
http://dx.doi.org/10.21125/inted.2020.1480
First experiences in the generation of reasonable feedback for Java beginners. - In: INTED 2020, (2020), S. 4383-4389
http://dx.doi.org/10.21125/inted.2020.1215
Mixed-integer-linear-programming model for the charging scheduling of electric vehicle fleets. - In: 2020 10th International Conference on Advanced Computer Information Technologies, (2020), S. 741-746
The number of electric vehicles is steadily increasing of the past few years. This transition to electric vehicles bears the challenge, to integrate the charging processes into the grid without overstressing it. To prevent this, research has tackled lately the scheduling of electric vehicle charging. Especially the charging of electric vehicle fleets is in the focus of research. There are already different solution approaches to increase the grid stability, to increase the intake of locally produced renewable energy or simply to reduce the cost. However, all these solution approaches use different mathematical models with different parameters to represent the charging scheduling problem. This results in the problem that each model is applicable for a special use case only, other use cases might need other parameters for the scheduling of the electric vehicle fleet. To ease this problem, this paper provides a detailed mathematical model for the cost minimization of a general electric fleet in the form of a mixed-integer-linearprogram. In order to do this, the paper shows that different research approaches use different parameters in their solutions. Afterwards, the paper presents a general overview of technical limitations for the electric fleets. On foundation of these limitations a mixed-integer-linear-program model for a wide range of electric fleets is established. Also, the paper provides options to extend the model in order to improve the result of an optimal schedule.
https://doi.org/10.1109/ACIT49673.2020.9208875