Dirk Söffker

University of Duisburg-Essen | uni-due · Chair of Dynamics and Control

A major aspect in the development of advanced driving assistance systems (ADASs) is the research in developing human driving behavior prediction and recognition models. Recent contributions focus on developing these models for estimating different driving behaviors like lane or speed change. Thus, the models are incorporated into the ADAS to genera...

The use of ultrasonic waves in the context of SHM offers methods to analyze materials and systems. Both Acoustic Emission-based approaches (passive, active) are limited by the propagation characteristics of ultrasonic waves, especially in inhomogeneous materials like carbon fiber reinforced polymers (CFRP). The use of the piezoelectric and inverse...

As one of the most relevant components in rotary machinery, ball bearings play an important role in diverse areas. To research bearing health state and remaining useful lifetime, several datasets have been developed. Among these datasets, Case Western Reserve University (CWRU) dataset is the most commonly used for bearing diagnosis. A large variety...

Vessel motion simulation as well as model-based accurate trajectory prediction of vessels require accurate models with respect to related dynamic properties. The ability to predict vessel’s trajectory behaviors will become relevant in the case of future autonomous navigation of vessels to predict the behavior of others. The definition of models or...

Deficit irrigation approaches have been applied in mitigation of pressure on global freshwater availability. Data from growth of plants under different water stress conditions allows the development of growth models taking into account irrigation scheduling. In this work, a model predictive control approach combined with a modified trellis decoding...

Current drones find a variety of applications, including in viticulture. The application of pesticides in steep slope viticulture is necessary to control pathogens. Due to the characteristics of the applied liquids, high demands are placed on the robustness and reliability of the drone and the selected sensors. For the application of the particle-l...

In this work, models for aquaculture are developed with regard to their relevance in an automated recirculation system. The three subsystems fish, water, and feed are determined as modular components. A selection of relevant variables is determined. The relationships between feed, water quality, and fish growth are described on the basis of an init...

In recent years, the development of advanced driving assistance systems (ADAS) has grown significantly within the transportation industry to assist drivers for making safe maneuvers. A major component in developing these assistance systems are driving behavior prediction and recognition models. These models aim to infer driving behaviors based on d...

Inner speech is a form of self-directed dialogue which plays an important role in cognitive development, speech monitoring, executive function, and psychopathology. Despite of a growing knowledge on its phenomenology, development, and function, approaches to the scientific study of inner speech have remained diffuse and largely unintegrated. Electr...

This contribution introduces a Transfer Learning (TL) approach for the diagnostic task to distinguish the ingredients of a typical production machine element: metalworking fluid (MWF). Metalworking fluids are oil or water-based fluids used during machining and shaping of metals to provide lubrication and cooling. Additives in MWF affect their perfo...

Human and machine contribute to the safety of human-machine systems, the interaction between the two is essential for the overall systems safety and reliability. Assuming (for-malized) knowledge about the structure of the interactions, monitoring of the human operator becomes possible so that the overall system of human and supervision system can c...

The focus of this contribution is to distinguish different Metalworking Fluid (MWF) with respect to different additives used for related formulations. Acoustic Emission (AE) measurements can be easily taken as process-close measures for evaluating cutting and forming processes as well as MWFs performance. In thread forming process, AE measurements...

Electric vehicles (EVs) are promising alternatives to carbonized propulsion-based vehicles. They are capable of reducing environmental degradation without compromising driving performance. Power management strategies (PMS) are particularly essential for electrified vehicles to ensure optimal power split between on-board energy storage sources and t...

Accurate vessel trajectory prediction is necessary for save and efficient navigation. Deep learning-based prediction models, esp. encoder-decoders, are rarely applied to inland navigation specifically. Approaches from the maritime domain cannot directly be transferred to river navigation due to specific driving behavior influencing factors. Differe...

In recent years, the need for networked and safe transport systems (vehicles, ships, trains, aircrafts) has increased. In inland waterway transport, remote-controlled operation controlled by a person at the same station on land, allows to increase the safety of traffic, might solve especially the problem of shortage of qualified nautical personnel,...

Autonomous vehicles like inland vessels require reliable information from on-board systems and surrounding objects like encountering vessels in the environment. Besides the detection of objects, the prediction of encountering object's trajectory is one of the most crucial tasks to realize safe operation of autonomous systems. In this contribution,...

Human behavior monitoring classically refers to the detection of human movements or a simple recognition of activities in limited known space. The monitoring of human activities in the context of concrete operating tasks often focuses on the detection of operating errors, unauthorized actions, or implicitly on the violation of protection goals. Thi...

The role played by humans is becoming more and more important as the proportion of human-related accidents is increasing in industry and traffic. Human error taxonomies and their applications in driving context improve the understanding of human error mechanisms in situated driving context. In previous works, the authors provide a human performance...

With a rapidly expanding global population placing an ever growing demand on freshwater resources, an increased focus on irrigation techniques tailored to the specific needs of plant appears as one solution to minimize overall freshwater consumption. Precision irrigation methods seek to realize an acceptable compromise between yield and irrigation...

Integrated systems with electric vehicles (EVs) and renewable energy sources are being widely considered as a first step building smart cities. A micro grid environment with wind, batteries, solar PV, and grid can be considered to together supply/store energy in the presence of EVs and home load demand. In such a case the role of an Energy Manageme...

Accepted paper: Tapping torque test (TTT) is a standardized evaluation approach for metalworking fluids' (MWFs) lubricity. Chemically different liquids measured according to the relevant standard ASTM D8288-19 often cannot be distinguished. In this contribution, the lubrication behavior of fluids affecting tapping torque and Acoustic Emission (AE)...

In this research, a new performance assessment based on the Probability of Detection (POD) reliability measure is developed integrating and discussing the effect of further parameters on classification results and therefore establishing a new connection between relevant process parameters and the related classifier evaluation. To illustrate the app...

Adaptive boosting (AdaBoost) algorithms fuse multiple weak classifiers to generate a strong classifier by adaptively determining the fusion weights of the weak classifiers. According to incorrect or correct classification results, sample weights become larger or smaller. However, this weight update scheme neglects valuable information in the result...

Data-driven control has received increasing attention by researchers in recent years because no system modeling procedure is required. By combination of data-driven and model predictive control, this paper discusses an improved model-free adap-tive predictive control approach with application to vibration reduction of an elastic crane. For system l...

Recentely accepted journal paper Adaptive boosting (AdaBoost) algorithms fuse multiple weak classifiers to generate a strong classifier by adaptively determining the fusion weights of the weak classifiers. According to incorrect or correct classification results, sample weights become larger or smaller. However, this weight update scheme neglects...

Vision-based object detection plays a crucial role for the complete functionality of many engineering systems. Typically, detectors or classifiers are used to detect objects or to distinguish different targets. This contribution presents a new evaluation of CNN classifiers in image detection using a modified Probability of Detection reliability mea...

With growth in the physical size of wind turbines, an increased structural loading of wind turbine components affecting operational reliability is expected. To mitigate structural loading in wind turbines, a novel strategy for structural load mitigation and rotor speed regulation of utility-scale wind turbines in above-rated wind speed region is pr...

Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads. The method allows accommodating unknown disturbance effects by using the combination of disturbance observers and disturbance rejection controllers. The actual main problem of DAC is t...

An automated driving system notifies a fallback-ready human driver to resume driving when critical operational and functional limits have been or are about to be exceeded. The point between notification and critical limit is the time budget. Previous studies indicate that interdependencies exist between takeover variables and the time budget leadin...

Variability of wind profiles in both space and time is responsible for fatigue loading in wind turbine components. Advanced control methods for mitigating structural loading in these components have been proposed in previous works. These also incorporate other objectives like speed and power regulation for above-rated wind speed operation. In recen...

Classifiers are useful and well-known machine learning algorithms allowing classifications. A classifier may be suited for a specific task depending on the application and data sets. To select an approach for a task, performance evaluation may be imperative. Existing approaches like the receiver operating characteristic and precision–recall curves...

Developing driving behavior prediction and recognition models play a crucial role in Advanced Driving Assistance Systems (ADAS). Developing these models generally requires the use of Machine Learning approaches. Often, Machine Learning approaches are difficult to interpret. In this contribution, an Artificial Neural Network (ANN)-based state machin...

Acoustic emission (AE) which describes the transient stress waves generated by the rapid release of energy from solid sources has been widely used in nondestructive testing (NDT) of materials and structures especially in health monitoring. As a class of deep neural networks, convolutional neural network (CNN) has applications in many fields. Severa...

In turbomachines, dry friction resulting from stator–rotor contacts is a severe problem that may degrade lifetime of the machine or even lead to complete failure. Knowledge about the system states and contact forces is beneficial for system monitoring or to prevent contacts through, e.g., active magnetic bearings. In this paper, a nonlinear model i...

Access link: https://authors.elsevier.com/a/1cyP84s9Hw2D~3 Wind energy takes an important role in the transformation of the global energy system towards clean and sustainable sources. The main development of wind energy technology in recent decades is the growth of wind turbine size motivated by economic factors. The larger turbine size helps incr...

Accepted paper: Current research and development in recognizing and predicting driving behaviors plays an important role in the development of Advanced Driver Assistance Systems (ADAS). For this reason, many machine learning approaches have been developed and applied. Hidden Markov Model (HMM) is a suitable algorithm due to its ability to handle ti...

Composite materials are frequently used due to light weight and high stiffness. However, the use of composite materials is limited due to several micro-mechanical damage mechanisms, which are currently not well understood. Therefore, Acoustic Emission (AE) is frequently suggested for in-situ diagnosis of composite materials in Structural Health Mon...

Monitoring the State-of-Health of vibrating mechanical systems is useful but complex. Besides challenges associated with dynamical behaviors of the systems monitored, supervision tasks are complex with respect data acquisition, feature extraction, and/or statistical modeling for feature classification. Data acquisition strategy addresses sensor typ...

Bearings are the most common mechanical components in machines. Once a bearing fails (or components in it), other adjacent components or the machine itself are effected up to failure. Therefore, bearing health condition is of great interest in practice. Several benchmark datasets are developed to evaluate development in bearings health state (diagn...

Considering technically complex systems, the evaluation of situations or conditions is a challenging task. To ensure a high accuracy assignments from different classifiers can be fused. To define requirements for a good fusion performance and to evaluate the potential for higher accuracy, in this paper the idea of a fictional classifier is introduc...

This article is addressed to the topic of robust state estimation of uncertain nonlinear systems. In particular, the smooth variable structure filter (SVSF) and its relation to the Kalman filter is studied. An adaptive Kalman filter is obtained from the SVSF approach by replacing the gain of the original filter. Boundedness of the estimation error...

Model predictive control (MPC) has become more attractive in control engineering for the last decades because of its efficiency and robustness. In this paper, an effective control strategy is proposed for vibration reduction of mechanical flexible systems in which establishment of a global dynamic model of the controlled system is not necessary. A...

Model-free control is a data-based control approach which can be applied when a dynamic model of the controlled system is difficult to obtain or identify. To realize the controller, a linearized data model is often established locally by using only input-output information from the closed-loop system. The data-based model contains a time-varying pa...

Research in understanding human behavior is a growing field within the development of Advanced Driving Assistance Systems (ADASs). In this contribution, a state machine approach is proposed to develop a driving behavior recognition model. The state machine approach is a behavior model based on the current state and a given set of inputs. Transition...

Automated inland shipping could be an attractive alternative transport option. Aspects related to transport cost and transport reliability can be improved by automated driving. The main idea of automation in this field is related to strengthen the competitiveness of inland shipping.

Mitarbeit in der Forschung des Fachgebiets Steuerung, Regelung und Systemdynamik (SRS). Das Projekt wird durch das Bundesministerium für Wirtschaft und Energie gefördert und in Zusammenarbeit mit dem Institut für Schiffstechnik, Meerestechnik und Transportsysteme (ISMT) und dem Fachgebiet Mechatronik (IMECH) der Universität Duisburg-Essen durchgefü...

In this paper a data-driven approach for model-free control of nonlinear systems with slow dynamics is proposed. The system behavior is described using a local model respectively a neural network. The network is updated online based on a Kalman filter. By predicting the system behavior two control approaches are discussed. One is obtained by calcul...

Power management in all-electric powertrains has a significant potential to optimally handle the limited energy and power density of electric power sources. Situation-based power management strategies (SB-PMSs), defining optimized solutions related to specific vehicle situations, offer the ability to reduce computational requirements and enhance th...

The future of electric vehicles relies nearly entirely on the design, monitoring, and control of the vehicle battery and its associated systems. Along with an initial optimal design of the cell/pack-level structure, the runtime performance of the battery needs to be continuously monitored and optimized for a safe and reliable operation and prolonge...

In this contribution automated interception of multiple targets based on object tracking is considered. An unknown amount of maneuvering targets is tracked using the multiple model Gaussian mixture probability hypothesis density filter. The approach utilizes converted measurements so that applicability to nonlinear measurement models is achieved. T...

Wind turbines growth in size and flexibility leads to increased structural loads. These loads affect the lifetime of the turbines and increase related maintenance cost. During the past decade, advanced control strategies have been developed and adopted effectively to mitigate structural loads. However, most of the attempts focus on the above-rated...

https://authors.elsevier.com/c/1aNwL,6t047IU8 Tapping torque test is a standardized (ASTM D5619-00) approach evaluating the lubricity of metalworking fluids. It was detected that running-in behaviors of taps and carryover effects caused by previously used fluids were not investigated. Further, it is detected that effects due to changed tap conditi...

ACCEPTED journal paper: Structural loads of wind turbines are becoming critical because of the growing size of wind turbines in combination with the required dynamic output demands. Wind turbine tower and blades are therefore affected by structural loads. To mitigate the loads while maintaining other desired conditions such as the optimization of...

Hybridized powertrains using two or more on-board power sources are getting increasing attention from researchers and automakers due to their ability to achieve equivalent performance to conventional vehicles and minimal harmful emissions. Power management systems (PMS) play a crucial role in hybrid powertrains to achieve high energy efficiency and...

This survey reviews recent researches conducted on the application of fuzzy approaches to Case-Based Reasoning (CBR) dealing with real-time applications. Fuzzy approaches have been effectively applied for knowledge representation, feature selection, and learning in CBR. Dealing with imprecise and uncertain knowledge, generalization, mining, and lea...

Accepted paper: Paperlink: https://rdcu.be/bJWNJ Autonomous or semi-autonomous aerial systems are used in different application domains to simplify or assist humans tasks. In this context, their behavior has to be verifiably safe. Here safe behavior denotes system's interaction with the environment with freedom from unacceptable risk for the env...

ACCEPTED JOURNAL PAPER: Random fluctuations of the nonlinearity curves of Fabry–Perot (F–P) tunable filters cause instabilities in fiber Bragg grating (FBG) interrogation systems. FBG sensors are widely used in structural health monitoring (SHM), and suppressing random fluctuations can provide engineers with more precise information on the conditio...

This paper presents a novel (Extended/Unscented) Kalman Filter by augmenting the event handling procedure of Ordinary Differential Equation (ODE) solvers with the predictor-corrector scheme of Extended/Unscented discrete Kalman Filter (EKF/UKF) introducing a variable step size Kalman Filter. This innovation allows a new quality of precision while o...

In this paper output constrained sliding mode control of nonlinear relative degree two systems is considered. The constraints are formulated with respect to the first derivative of the control variable. The system may be effected by matched disturbances. Only the uncertainty bounds are required to be known. A multi-controller approach with variable...

In the field of model predictive control (MPC), the computational effort of solving the optimization problem considering long prediction horizon is often challenging, making the implementation in real time infeasible. On the other side, a longer prediction horizon leads to better control performance. Therefore, a trade off between computational eff...

Model-free adaptive control has been used to design feedback in cases when accurate mathematical modeling of the system can not be realized. By using only input-output information, the control approach is attractive with respect to minimal design efforts. In this contribution an improved model-free control program is proposed and applied to flexibl...

In this paper chattering mitigated sliding mode control of uncertain nonlinear systems is considered. Concrete knowledge about the system parameters or uncertainty bounds is assumed to be unavailable. A combined sliding mode and data-driven model-free predictive control strategy is proposed. Calculation of the predictive control input is based on a...