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In observer-based control integral or controller windup can systematically be prevented by the observer technique, i.e., by feeding the saturated plant input signal into the observer. This prevents all windup effects caused by the dynamics of the compensator. The possibly remaining windup effects are then the same as if constant state feedback control had been applied. When using the classic approach for robust rejection of persistent disturbances the state-plus-disturbance observer is subdivided into the state observer and the controlled signal model. Thus the observer technique is only applicable when taking additional measures or when resorting to a recently published dual design method. Here, a very simple design for MIMO PI compensators is suggested which directly yields the basis for the observer technique.

Nonlaminated magnetic actuators are highly influenced by eddy currents and minor perturbations like e. g. hysteresis. Known analytical models lead to trans-cendental system descriptions with fractional-order characteristics, not suited for the actuator control. Although analytical approximations resolve the issue, the inclusion of minor perturbations leads to impractical model orders, which require simplifications and compromise the model accuracy. This article studies numerical methods to directly approximate the transcendental systems or measurement data, allowing for a high accuracy with sufficiently low orders. We improve existing approaches like Levy’s method and vector fitting and apply them to a fractional-order system. Using measurement data, a comparison shows that the numerical approaches match or excel our previously studied analytical approximations.

To facilitate the planning of product processes, the Formalized Process Description (FPD) model was proposed. It enables users to graphically describe the requirements of a production process. However, the FPD model has limits. To overcome these limits, this paper describes an extension of the FPD model, which is called the Extended FPD model. The objects in the Extended FPD model are assigned types and logical statements to represent their specifications. Hence, the expressive power of the FPD model is enhanced. In this paper, a formal definition of the Extended FPD model is also presented. Based on this definition, a set of rules is defined to detect the contradictions automatically in the Extended FPD model. In addition, the description of requirements by using the Extended FPD model can also enable the integration of more formal verification methods.

Zusammenfassung Um bereits in der Konzeptphase autonomer Fahrzeuge einen fundierten Eindruck bestehender Risikopotenziale zu erhalten, werden im Zuge von deduktiven und induktiven SOTIF-Analysen mögliche auslösende Umstände für gefährliches Verhalten untersucht. In diesem Zusammenhang wird in der ISO 21448 die Durchführung einer systemtheoretischen Prozessanalyse (STPA) vorgeschlagen. In diesem Beitrag führen wir deutsche Terminologie für SOTIF-Betrachtungen ein und setzen uns im Zuge einer Anwendung kritisch mit der STPA-Theorie auseinander, wobei wir begleitend methodische Ergänzungen anregen.

Robotic systems require holistic capabilities to sense, perceive, and act autonomously within their application environment. A safe and trustworthy autonomous operation is essential, especially in hazardous environments and critical applications like autonomous construction machinery for the decontamination of landfill sites. This article presents an enhanced combination of machine learning (ML) methods with classic artificial intelligence (AI) methods and customized validation methods to ensure highly reliable and accurate sensing and perception of the environment for autonomous construction machinery. The presented methods have been developed, evaluated, and applied within the Competence Center »Robot Systems for Decontamination in Hazardous Environments« (ROBDEKON) for investigating and developing robotic systems for autonomous decontamination tasks. The objective of this article is to give a holistic, in-depth overview for the ML-based part of the perception pipeline for an autonomous construction machine working in unstructured environments.

Zusammenfassung Das VGF-Verfahren ist ein moderner Prozess zur Züchtung von Einkristallen, der Grundlage für nahezu alle elektronischen Anwendungen. Die sukzessive Erstarrung der Schmelze zum Einkristall wird dabei durch geeignete Ansteuerung der als Aktoren in der Anlage zur Verfügung stehenden Heizer realisiert. Dieses Regelungsproblem ist Gegenstand des Beitrags, wobei der Schwerpunkt auf einer anschaulichen und einführenden Darstellung der Thematik und weniger den mathematischen Details liegt. Basierend auf einem Modell des Kristallzüchtungsprozesses, das partielle Differentialgleichungen für die Wärmediffusion in Schmelze und Kristall beinhaltet und aufgrund der Übergangsbedingung an der Phasengrenze als zweiphasiges Stefan-Problem bezeichnet wird, werden zwei Entwürfe von Folgereglern vorgestellt. Ein flachheitsbasierter Ansatz nutzt eine endlichdimensionale Approximation des Modells, während eine mittels Backstepping entworfene Zustandsrückführung unendlichdimensional ist. Beide Regler werden in umfangreichen Simulationsstudien validiert und miteinander verglichen.

This work presents an approach to activate vehicle safety systems based on a pre-crash prediction. It focuses on the three major topics namely, crash validation, the geometry-estimation, and the crash severity and restraint strategy prediction. The topic of crash validation is administered by a proposal of a novel contact-based validation sensor along with the experimental investigations for comparison with other sensors.