Thorsten Pawletta

• Dr.-Ing.
• Professor at Wismar University of Applied Sciences

NSA-DEVS (Non-Standard Analysis Discrete Event System Specification) is an advancement of the DEVS formalism for modeling and simulating discrete-event and hybrid systems. DEVS supports modular-hierarchical modeling and clearly separates model from simulator. The primary objective of NSA-DEVS is to simplify the modeling of components with Mealy beha...

The PDEVS formalism is widely used for the description and analysis of discrete event systems. But PDEVS has some drawbacks in modeling Mealy behavior. A revised version (RPDEVS) has been invented to resolve them, but it has problems of its own, mainly because of its complicated simulator structure. The recently proposed NSA-DEVS scheme tries to un...

The recently proposed NSA-DEVS formalism uses infinitesimal time delays to combine the easy implementation of Mealy components from RPDEVS with the simple simulator structure of PDEVS in order to make DEVS a suitable foundation for complex component-based modeling tasks. To prove its general applicability, it is used here to implement a large real-...

The paper presents a methodological approach for using reinforcement learning analogously to other numerical methods in simulation based experiments using the concept of experimental frame.

Reinforcement Learning (RL) is an optimization method from the field of Machine Learning. It is characterized by two interacting entities referred to as the agent and the environment. The agent influences the environment through actions and the environment responds with state information and reward values. The goal of RL is to learn how an agent sh...

The SCS M&S Body of Knowledge is a living concept, and core research areas are among those that will drive its progress. In this chapter, conceptual modeling constitutes the first topic, followed by the quest for model reuse. As stand-alone applications become increasingly rare, embedded simulation is of particular interest. In the era of big data,...

In this chapter, we provide an introductory view for the scope of the SCS M&S Body of Knowledge, including the terminology. We provide a rationale for the theoretical basis of M&S and give an overview of the modeling and simulation framework (MSF) applied in many contributions, followed by the basic system entity structure (SES) concepts.KeywordsMo...

To utilize the PDEVS formalism for the practical modeling and simulation of discrete-event systems, the recently proposed variant NSA-DEVS combines the Mealy behaviour of RPDEVS with a simple simulator algorithm by employing infinitesimal time delays. To further test the practical usefulness of this new approach, four simple systems showing non-tri...

The PDEVS formalism is widely used for the description and analysis of discrete event systems. But PDEVS has some drawbacks in modeling Mealy behavior. A revised version (RPDEVS) has been invented to resolve them, but it has problems of its own, mainly because its complicated simulator structure. The recently proposed NSA-DEVS scheme tries to unite...

This paper deals with the extension of a Python-based infrastructure for studying the characteristics and behavior of families of systems. The infrastructure allows automatic execution of simulation experiments with varying system structures as well as with varying parameter sets in different simulators. Special focus is put on the support of diffe...

The recently published ARGESIM benchmark C22 'Non-standard Queuing Policies' studies three queuing models, where the queues utilize more complex policies than the standards FIFO, LIFO or priority. Jockeying queues allow entities to switch to a shorter queue, in reneging queues entities leave a queue after a maximal waiting time, and classing queues...

This paper deals with the extension of a Python-based infrastructure for studying the characteristics and behavior of families of systems. The infrastructure allows automatic execution of simulation experiments with varying system structures as well as with varying parameter sets in different simulators. Special focus is put on the support of diffe...

System Entity Structures (SES) are used to define families of systems. In this context they are employed in combination with a model base (MB) to describe a set of simulation models. Using a framework, simulation models are generated from the SES/MB in a goal-oriented manner, executed and their results analyzed. The entire process is automated, ite...

System entity structure has been used since the 1970s as a formal ontology framework, axiomatically defined, to represent the elements of a system of systems and their hierarchical relationships resulting in a family of hierarchical models. One challenge with this approach is the process of exploring a family of hierarchical models, and selecting a...

For some time, the focus of past research on industrial workplace designs has been the optimization of processes from the technological point of view. Since human workers have to work within this environment the design process must regard Human Factor needs. The operators are under additional stress due to the range of high dynamic processes and du...

The ARGESIM benchmark C22 'Non-standard Queuing Policies' deals with queueing systems, where entities can leave a queue in a dynamically changed order. It is solved here with MatlabGPSS, a Matlab-based implementation of the well-known GPSS modeling language. Though quite old, it still has its merits, such as precisely defined and flexible methods t...

This paper proposes a Python-based infrastructure for studying the characteristics and behavior of families of systems. The infrastructure allows automatic execution of simulation experiments with varying system structures as well as with varying parameter sets in different simulators. Possible system structures and pa-rameterizations are defined u...

The ARGESIM benchmark C22 ’Non-standard Queuing Policies’ studies three non-standard queues that provide different ways to access entities inside a queue like detaching elements or reorder them: The reneging queue, where entities leave a queue after a given waiting time, the jockeying queue, where entities can switch to another shorter queue, and t...

The System Entity Structure (SES) is a high level approach for variability modeling, particularly insimulation engineering, which is under continuous development. In this context, an enhanced framework is introduced that supports dynamic variability evolution using the SES approach. However, the main focus is to start a discussion about a set of de...

This paper proposes a Python-based infrastructure for studying the characteristics and behavior of families of systems. The infrastructure allows automatic execution of simulation experiments with varying system structures as well as with varying parameter sets in different simulators. Possible system structures and parametrizations are defined usi...

Currently, greater attention is paid to the nature of work and workplaces within the digitized industry due to the increasing complexity of work tasks. The operators are under additional stress due to the range of high dynamic processes and due to the integration of robots and autonomous operating machines. There have been few studies on how Human...

Reinforcement-Learning (RL) has become a bigger task in engineering. The advantage of RL is the ability to learn without known datasets, only with rules included in an environment. If the task becomes bigger, the learning phase grows enormously. Two approaches for accelerating the time of learning are discussed in this work. Introducing interim rew...

Machine-Learning (ML) ndet derzeit auch in ingenieur-technischen Anwendungen eine große Beach-tung. Als problematisch erweist sich dabei häug der erforderliche Rechenaufwand. Im Beitrag wer-den Beschleunigungspotentiale für ein Reinforcement-Learning-Verfahren untersucht. Neben Ansätzen der Parallelverarbeitung wird auch das Beschleunigungspo-tenti...

This paper describes how a complex case study for variability modeling and simulation from the documentation of MATLAB/Simulink can be remodeled with the extended System Entity Structure and Model Base (eSES/MB) approach using the Phython-based tool SESToPy and the accompanying modelbuilder SESMoPy.

The System Entity Structure (SES) is a high level approach for variability modeling, particularly in simulation engineering. An SES describes a set of system congurations, i.e. different system structures and parameter settings of system components. In combination with a Model Base (MB), executable models can be generated from an SES. Based on an e...

This paper describes how a complex case study for variability modeling and simulation from the documentation of MATLAB/Simulink can be remodeled with the extended System Entity Structure and Model Base (eSES/MB) approach using the Phython-based tool SESToPy and the accompanying modelbuilder SESMoPy.

20 min presentation showing the differences in variant modeling using the System Entity Structure / Model Base (SES/MB) approach in contrast to implementing an 150%-model.

Model engineering aims at applying systematic, standardized, and quantifiable methodologies to model life cycles for achieving minimum cost and maximum quality. This chapter addresses quality analysis, assessment and improvement approaches, and methodologies for graphical models. It introduces modeling guidelines, model checking and repair, model r...

Versatile systems are characterized by a high degree of variability, regarding configuration and customization for employment in a particular context, and reactive adaptability during operation. In engineering, cyber-physical systems and flexible, reconfigurable, or adaptable production systems are typical examples. Their development requires enhan...

The paper investigates how a robot control for a pick-and-place application can be learned by simulation using the Q-Learning method, a special Reinforcement Learning approach. Furthermore, a post-optimization approach to improve a learned strategy is presented. Finally, it is shown how the post-optimized strategy can be automatically transformed i...

The System Entity Structure (SES) is a high level approach for variability modeling, particularly in simulation engineering, which is under continuous development. In this context, an enhanced framework is introduced that supports dynamic variability evolution using the SES approach. However, the main focus is to start a discussion about a set of d...

Es wird untersucht, wie mit Hilfe des Q-Learning-Verfahrens, einem speziellen Reinforcement-Learning-Ansatz, simulationsbasiert eine Robotersteuerung für eine Pick- und-Place-Anwendung erlernt werden kann. Weiterhin wird ein Postoptimierungsansatz zur Verbesserung einer erlernten Strategie vorgestellt. Anschließend wird gezeigt, wie die postoptimie...

The complexity is becoming the future landscape of technical systems. Emergence is defined as the coherent and novel macro-level patterns, properties, behavior or structures that arise from the micro level interactions among the elements of the complex systems. It is a self-organized order. Self-organization can be pronounced as a designed system c...

Avionics, like any other safety-critical real-time systems, pose unique challenges on system design, development, and testing. Specifically, the rigorous certification process mandated for avionics software calls for additional attention. The DO-178C Software Considerations in Airborne Systems and Equipment Certification provides detailed guideline...

The System Entity Structure (SES) is a high level approach for variability modeling, particularly in simulation engineering, which is under continuous development. In this context, an enhanced framework is introduced that supports dynamic variability evolution using the SES approach. However, the main focus is to start a discussion about a set of d...

The Simulation Based Control (SBC) framework is intended for rapid control development. It supports a seamless control development from the early design phase to the operation phase. The poster illustrates the application of the framework for developing task oriented controls for heterogeneous multi-robot systems using the Robotic Control and Visua...

The turnaround in energy policy is an ambitious intention for the German society. Especially the efficient usage of volatile energy sources, like wind and solar energy, is a big challenge. However, one solution to tackle this problem is the smart demand management. That means, to adjust the energy demand to the energy supply. Nowadays, in the field...

The System Entity Structure (SES) is a high level approach for variability modeling, particularly in simulation engineering. The SES is under continuous development. In this context, an enhanced framework is introduced that supports dynamic variability evolution using the SES approach and connects the SES to a model base (MB). Using this framework...

In the design of manufacturing systems the consideration of resource usage, especially energy consumption, is getting more attention. However, the inclusion of all relevant physical processes in a unified modeling approach is a non-trivial task, if detailed analyses are required. The commonly used modeling approach for manufacturing systems is the...

Model-based engineering is defined as the pragmatic utilization of model-based practices, namely, modeling, metamodeling and model transformations in various steps of engineering. In the last decade, the simulation of technical systems has leveraged graphical modeling and model-to-text transformations, but metamodeling and model transformation prac...

MATLAB/Simulink is a popular software environment used by engineers and scientists. It offers integrated modeling and simulation tools and numerous toolboxes employable in conjunction with modeling and simulation tasks. However, modeling and simulation of discrete event systems is often confusing and sometimes not compliant with the established sys...

The tutorial introduces into basics of the System Entity Structure (SES) Ontology, originally introduced by B.P. Zeigler. Additionally, some extensions of the SES Ontology will be introduced to make it more pragmatic for variability modeling of complex systems. Afterwards, two prototypes of new software tools for designing SES models will be presen...

In der Steuerungsentwicklung haben sich Entwurfsmethodiken wie der Rapid Control Prototyping (RCP) An-satz etabliert. Die Steuerungssoftware (CS) wird durchgehend modellbasiert in möglichst einer Softwareum-gebung entwickelt. Beginnend in der frühen Entwurfsphase, wird ein Simulationsmodell (SM) schrittweise zu einer CS ausgebaut. Die Überführung i...

While any simulation study starts with a scenario, scenario development is usually conducted in an unstructured and ad hoc manner. In order to streamline scenario development, a formal approach is envisioned in the research flight simulator facility of German Aerospace Center (DLR), namely Air Vehicle Simulator (AVES). System Entity Structure (SES)...

The simulation-based study of Cyber-Physical Systems or complex production systems leads often to a vast amount of system variants. Each system variant is characterized by a particular model structure and parameter settings, although system variants may also share common parts. There are two main approaches for modeling such a set of system variant...

The increasing complexity of systems entails an increasing complexity of simulation models. Likewise, heterogeneity in system components corresponds to heterogeneous simulation models. Cyber physical systems (CPS) represent an emerging class of technical systems characterized by their complexity and heterogeneity. Developing simulation models for C...

Robot programming software is mostly proprietary and cannot be used for other manufacturers' robots. Nevertheless, there is a desire to allow interactions between robots being developed by different manufacturers in order to set up a Multi-Robot System (MRS). An MRS refers to a team consisting of interacting industrial robots which share skills to...

Software product-lines are designed to tackle the development of systems that are characterized by a high degree of variability. They define variation points where different solutions can be derived for different products. Such variability mechanisms can be defined at different levels of abstraction, ranging from requirements specification to sourc...

In the design of manufacturing processes the consideration of resource usage, especially energy consumption , is getting more attention. However, the inclusion of the relevant physical processes in a unified modeling approach is often a non-trivial task. The commonly used simulation tools in this domain usually only support discrete event modeling...

Industrial robots are used in various fields of application and many robot manufacturers are active in the market. In most cases, their software solutions are proprietary and, consequently, they cannot be used for third party robots. Moreover, the integration of external hard- or software is highly restricted. Long term standardization efforts for...

Editorial SNE Special Issue ‘Simulation of Technical Systems – Methods, Tools & Applications’ Modelling and Simulation is an important approach for development and operation of technical systems for many years. Accordingly, the ASIM sections Simulation of Technical Systems and Foundations and Methods in Modelling and Simulation organize an annual w...

Simulator fidelity has been defined as the conformance of a flight simulator to the characteristics of the real aircraft. Objective fidelity evaluation is an engineering approach that attacks the fidelity problem with comparison of simulator and the actual system behavior over some quantitative measures. Testing can be pronounced as the fundamental...

Industrial robots are used in various fields of application and many robot manufacturers are active in the market. In most cases, their software solutions are proprietary and, consequently, they cannot be used for third party robots. Moreover, the integration of external hard-or software is highly restricted. Long term standardization efforts for r...

Softwarelösungen zur Programmierung von Robotersystemen sind heutzutage zumeist herstellerspezifisch und lassen sich nicht für Roboter anderer Hersteller verwenden. Dennoch besteht der Wunsch unterschied-liche Interaktionen zwischen Robotern verschiedener Hersteller zu ermöglichen. Ausgehend von einer Analyse möglicher Interaktionsprinzipien für In...

In modeling and simulation, Validation and Verification (V&V) have always attracted significant interest. With Model Based Development (MBD) testing models became a part of product V&V. Model-Based Testing (MBT) is an advanced approach for automating the testing process for flexibility and adaptability. MBT advocates utilization of models for the s...

In computer science ontology is often understood as a formal specifi cation of a shared conceptualization in form of a model. The considered doma in of conceptualiza tion is mod eling and simulation of modular, hierarchical systems . In this context , the System Entity Structure (SES) Ontology has been introduced for specifying a set of various sys...

Industrial robots are used in various application fields and many robot manufacturers are active on the market. In most cases, their software solutions are proprietary and thereby they cannot be used for third party robots. Moreover, the integration of external hard- or software is highly restricted. Long term standardization efforts for robot prog...

Industrial robots are used in various application fields and many robot manufacturers are active on the market. In most cases, their software solutions are proprietary and thereby they cannot be used for third party robots. Moreover, the integration of external hard- or software is highly restricted. Long term standardization efforts for robot prog...

Abstract. The modular-hierarchical modeling subdivides a system into dynamic describing atomic, and structure describing coupled systems. Due to the usally static structure of coupled systems, it can sometimes hard to realize a component-oriented mapping of real system elements in model components. Hence, several approaches to model structural chan...

The term simulator fidelity has become enormously important in the scope of simulation research, when assessing training efficiency and the transfer of training to real flight. It is defined as the degree to which a flight simulator matches the characteristics of the real aircraft. Objective simulator fidelity provides an engineering standard, by a...

Neben den logistischen und produktionstechnischen Größen spielt der Ressourcenverbrauch bei der Ausle- gung fertigungstechnischer Prozessketten in einer ereignisdiskreten Simulationsumgebung eine wesentliche Rolle. Hierzu wurden Methoden zur Beschreibung der Ressourcenverbräuche entwickelt. Bisherige Model- lierungsansätze basieren auf der messtech...

Die Ontologie-unterstützte Systemmodellierung kombiniert die klassische systemtheoretische Modellierung mit einer ontologischen Systemspezifikation. Konfigurierbare dynamische Modelle mit definierten Ein-/ Ausgangsschnittstellen werden in einer Modellbasis organisiert. Die Ontologie beschreibt deklarativ für ei-nen Gegenstandsbereich wie aus den dy...

The term simulator fidelity has become enormously important in the scope of simulation research, when as-sessing training efficiency and the transfer of training to real flight. It is defined as the degree to which a flight simulator matches the characteristics of the real aircraft. Objective simulator fidelity provides an engineering standard, by...

Editorial SNE Special Issue ‘Ontologies in Modeling and Simulation’ In the last 10 years, the advances in semantic web have influenced modeling and simulation (M&S). Gruber’s definition that “ontology is a formal specification of conceptualization” has been well accepted by the M&S community. In 2004, Miller, et al. first introduced how ontologies...