### Refine

#### Document Type

- Conference Proceeding (20)
- Article (4)
- Patent (1)

#### Is part of the Bibliography

- yes (25)

#### Institute

- Technik (25)

#### Publisher

- IEEE (13)
- Apprimus Wissenschaftsverlag (2)
- Academic Publications Ltd. (1)
- Berlin ; Offenbach (1)
- British Institute of Non-Destructive Testing (1)
- GRID-FTN (1)
- Hochschulen für Angewandte Wissenschaften Baden-Württemberg, Koordinierungsstelle (1)
- Public Verlagsgesellschaft (1)
- The British Institute of Non-Destructive Testing (1)
- VDE VERLAG GMBH (1)

In this article feedback linearization for control-affine nonlinear systems is extended to systems where linearization is not feasible in the complete state space by combining state feedback linearization and homotopy numerical continuation in subspaces of the phase space where feedback linearization fails. Starting from the conceptual simplicity of feedback linearization, this new method expands the scope of their applicability to irregular systems with poorly expressed relative degree. The method is illustrated on a simple SISO–system and by controlling the speed and the rotor flux linkage in a three phase induction machine.

Methods for increasing the energy efficiency of induction motors by an appropriate control strategy have been a subject of research during the last years. Several methods for loss minimization have been developed for induction motors operated in a steady state. In recent years, some solutions for the dynamic case have been given as well either using an online or offline optimization approach, implying a certain computational burden, which is undesired in practice. This paper shows that the appropriate application of steady state techniques during transients due to a changing motor torque is a suboptimal strategy with an acceptable performance for efficiency optimization given an induction machine where saturation effects of the main inductance must be considered. The optimization problem is simplified such that a simple suboptimal solution is possible and the quality of the suboptimal solution is investigated by simulations and measurements. The proposed solution is simple, easy to implement, and does not require an online optimization. In addition, the influence of magnetizing induction saturation is considered.

The current paper discusses the optimal choice of a filter time constant for filtering the steady state flux reference in an energy efficient control strategy for changing load torques. It is shown that by appropriately choosing the filter time constant as a fraction of the rotor time constant the instantaneous power losses after a load torque step can be significantly reduced compared to the standard case. The analysis for the appropriate choice of the filter time constant is based on a numerical study for three different induction motors with different rated powers.

Energy efficient electric control of drives is more and more important for electric mobility and manufacturing industries. Online dynamic optimization of induction machines is challenging due to the computational complexity involved and the variable power losses during dynamic operation of induction machines. This paper proposes a simple technique for sub-optimal online loss optimization using rotor flux linkage templates for energy efficient dynamic operation of induction machines. Such a rotor flux linkage template is given by a rotor flux linkage trajectory which is optimal for a specific scenario. This template is calculated in an offline optimization process. For a specific scenario during real time operation the rotor flux linkage is calculated by appropriately scaling the given template.

This paper discusses the optimal control problem for increasing the energy efficiency of induction machines in dynamic operation including field weakening regime. In an offline procedure optimal current and flux trajectories are determined such that the copper losses are minimized during transient operations. These trajectories are useful for a subsequent online implementation.

Steady state efficiency optimization techniques for induction motors are state of the art and various methods have already been developed. This paper provides new insights in the efficiency optimized operation in dynamic regime. The paper proposes an anticipative flux modification in order to decrease losses during torque and speed transients. These trajectories are analyzed based on a numerical study for different motors. Measurement results for one motor are given as well.

In diesem Beitrag wurde gezeigt, wie mit Hilfe von Verfahren zur Analyse von Petri–Netzen ein in der Programmiersprache Kontaktplan erstelltes SPS–Programm analysiert werden kann. Das Ziel des Verfahrens ist dabei nicht eine Verifikation im eigentlichen Sinne sondern das Aufdecken von verbotenen oder unerwünschten Zuständen. Im Beitrag wurden Regeln zur Transformation des im Kontaktplan erstellten Ablaufs in ein Petri–Netz angegeben und anhand der Analyse eines fehlerhaft implementierten Ablaufs die Leistungsfähigkeit des Ansatzes vorgestellt. Das Beispiel zeigt, dass Programmfehler bereits vor einem Test an der realen Anlage erkannt werden können. Bei der weiteren Entwicklung des Verfahrens liegt ein Schwerpunkt auf der Verallgemeinerung auf im Kontaktplan entwickelte Programmorganisationseinheiten, die nicht nur reine
Abläufe implementieren. Ein weiterer wichtiger Entwicklungsschritt ist die graphische Unterstützung der Fehlersuche im Erreichbarkeitsgraphen, so dass insgesamt ein leistungsfähiges Werkzeug zur Unterstützung der Implementierung von Ablaufsteuerungen im Kontaktplan zur Verfügung steht.

Condition Monitoring for mechanical systems like bearings or transmissions is often done by analysing frequency spectra obtained from accelerometers mounted to the components under observation. Although this approach gives a high amount on information about the system behaviour, the interpretation of the resulting spectra requires expert knowledge, that is, a deep understanding of the effect on condition deterioration on the measured spectra. However, an increasing number of condition monitoring applications demands other representations of the measured signals that can be easily interpreted even by non–experts. Therefore, the objective of this paper is to develop an approach for processing measured process data in order to obtain an easy to interpret measure for assessing the component condition. The main idea is to evaluate the deterioration of a component condition by computing the correlation function of current measurements with past measurements in order to detect a component condition deterioration from a change in these correlation functions. Besides the simplicity of the obtained measure, this approach opens the opportunity for integrating a model based approach as well. The developed method is tested based on a condition monitoring application in a roller chain.

This paper describes a new method for condition monitoring of a roller chain. In contrast to conventional methods, no additional accelerometers are used to measure and interpret frequency spectra but the chain condition is evaluated using an easy to interpret similarity measure based on correlation functions using the driving motor torque. An additional clustering of current data and reference measurements yields an easy to understand representation of the chain condition.

One of the challenges in condition monitoring systems is the residual life time prediction. This prediction is done based on statistical methods, based on physical knowledge about the considered process or a combination of these approaches. Physical knowledge of the system is a result of long-term experience of process operators. However, it can be gained as well by analyzing appropriately designed process models. The additional benefit of such models is that particular effects and their impact on the process behavior can be analyzed in detail and without plant operation in a shorter time. The current contribution developed in the framework of the research project Model Based Hierarchic Condition Monitoring presents such models for condition monitoring of roller chains. First, already existing high order dynamic models given by nonlinear differential equations of such chains are extended to incorporate effects that occur due to a deterioration of the chain condition. Then, a simple model is developed and compared to the high order model. Based on the two models the change in the process behavior due to a deterioration of the roller chain condition is analyzed to illustrate that these models can be used in future research in the above mentioned research project to better predict the residual life time of the considered roller chains.