The disturbance model in model based predictive control

Model Based Predictive Control (MBPC) is a control methodology which uses a process model on-line in the control computer; this model is used for calculating output predictions and optimizing control actions. The importance of the system model has been generally recognized, but less attention has been paid to the role of the disturbance model. In this paper the importance of the disturbance model is indicated with respect to the EPSAC approach to MBPC. To illustrate this importance, an example of this advanced control methodology applied to a typical mechatronic system is presented, to compare the performances obtained by using different disturbance models. It clearly shows the benefits of using an "intelligent" disturbance model instead of the "default" model generally adopted in practice

Acute stress response for self-optimizing mechatronic systems

Self-optimizing mechatronic systems react autonomously and flexibly to changing conditions. They are capable of learning and optimize their behavior throughout their life cycle. The paradigm of self-optimization is originally inspired by the behavior of biological systems. The key to the successful development of self-optimizing systems is a conceptual design process that precisely describes the desired system behavior. In the area of mechanical engineering, active principles based on physical effects such as friction or lever are widely used to concretize the construction structure and the behavior. The same approach can be found in the domain of software-engineering with software patterns such as the broker-pattern or the strategy pattern. However there is no appropriate design schema for the development of intelligent mechatronic systems covering the needs to fulfill the paradigm of self-optimization. This article proposes such a schema called Active Patterns for Self-Optimization. It is shown how a catalogue of active patterns can be derived from a set of four basic active patterns. This design approach is validated for a networked mechatronic system in a multiagent setting where the behavior is implemented according to a biologically inspired technique – the neuro-fuzzy learning method.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Mechatronics and Computer ClustersRed de Universidades con Carreras en Informática (RedUNCI

Architecture and Design Methodology of Self-Optimizing Mechatronic Systems

The conceivable development of information and communication technology will enable mechatronic systems with inherent partial intelligence. We refer to this by using the term \"self-optimization\". Self-Optimizing systems react autonomously and flexibly on changing operation conditions. They are able to learn and optimize their behavior at runtime. The development of mechatronic and especially self-optimizing systems is still a challenge. A significant milestone within the development is the principle solution. It determines the basic structure as well as the operation mode of the system and is the result of the conceptual design. Additionally it is the basis for the concretization of the system which involves experts from several domains, such as mechanics, electrical engineering/electronics, control engineering and software engineering. This contribution presents a new specification technique for the conceptual design of mechatronic and self-optimizing systems. It also uses the railway technology as a complex example, to demonstrate how to use this specification technique and in which way it profits for the development of future mechanical engineering systems. Keywords Design Methodology, Mechatronics, Self-Optimization, Principle Solution, Conceptual Design, Domain-Spanning Specificatio

Optimal Performance of Modular and Synchronized Mechatronic Systems

Optimizing the configuration and overall performance of synchronized modular systems is considered in this paper. The synchronized modules can be considered as a hybrid system, including continuous-time dynamics of local moving devices, combined with high-level discrete event sequences. The continuous-time trajectories are approximated by the Gauss pseudospectral method, resulting in a nonlinear programming (NLP) problem. The optimal configuration generates the maximal production rate subject to dynamic constraints. A complete design procedure is presented and applied to a case study of a packaging machine, where an alternative optimal configuration is achieved compared to current industrial practices

Fujaba days 2009 : proceedings of the 7th international Fujaba days, Eindhoven University of Technology, the Netherlands, November 16-17, 2009

Fujaba is an Open Source UML CASE tool project started at the software engineering group of Paderborn University in 1997. In 2002 Fujaba has been redesigned and became the Fujaba Tool Suite with a plug-in architecture allowing developers to add functionality easily while retaining full control over their contributions. Multiple Application Domains Fujaba followed the model-driven development philosophy right from its beginning in 1997. At the early days, Fujaba had a special focus on code generation from UML diagrams resulting in a visual programming language with a special emphasis on object structure manipulating rules. Today, at least six rather independent tool versions are under development in Paderborn, Kassel, and Darmstadt for supporting (1) reengineering, (2) embedded real-time systems, (3) education, (4) specification of distributed control systems, (5) integration with the ECLIPSE platform, and (6) MOF-based integration of system (re-) engineering tools. International Community According to our knowledge, quite a number of research groups have also chosen Fujaba as a platform for UML and MDA related research activities. In addition, quite a number of Fujaba users send requests for more functionality and extensions. Therefore, the 7th International Fujaba Days aimed at bringing together Fujaba developers and Fujaba users from all over the world to present their ideas and projects and to discuss them with each other and with the Fujaba core development team

Modeling and control of the starter motor and start-up phase for gas turbines

Improving the performance of industrial gas turbines has always been at the focus of attention of researchers and manufacturers. Nowadays, the operating environment of gas turbines has been transformed significantly respect to the very fast growth of renewable electricity generation where gas turbines should provide a safe, reliable, fast, and flexible transient operation to support their renewable partners. So, having a reliable tools to predict the transient behavior of the gas turbine is becoming more and more important. Regarding the response time and flexibility, improving the turbine performance during the start-up phase is an important issue that should be taken into account by the turbine manufacturers. To analyze the turbine performance during the start-up phase and to implement novel ideas so as to improve its performance, modeling, and simulation of an industrial gas turbine during cold start-up phase is investigated this article using an integrated modular approach. During this phase, a complex mechatronic system comprised of an asynchronous AC motor (electric starter), static frequency converter drive, and gas turbine exists. The start-up phase happens in this manner: first, the clutch transfers the torque generated by the electric starter to the gas turbine so that the turbine reaches a specific speed (cranking stage). Next, the turbine spends some time at this speed (purging stage), after which the turbine speed decreases, sparking stage begins, and the turbine enters the warm start-up phase. It is, however, possible that the start-up process fails at an intermediate stage. Such unsuccessful start-ups can be caused by turbine vibrations, the increase in the gradients of exhaust gases, or issues with fuel spray nozzles. If, for any reason, the turbine cannot reach the self-sustained speed and the speed falls below a certain threshold, the clutch engages once again with the turbine shaft and the start-up process is repeated. Consequently, when modeling the start-up phase, we face discontinuities in performance and a system with variable structure owing to the existence of clutch. Modeling the start-up phase, which happens to exist in many different fields including electric and mechanical application, brings about problems in numerical solutions (such as algebraic loop). Accordingly, this study attempts to benefit from the bond graph approach (as a powerful physical modeling approach) to model such a mechatronic system. The results confirm the effectiveness of the proposed approach in detailed performance prediction of the gas turbine in start-up phase

Emerging Trends in Mechatronics

Mechatronics is a multidisciplinary branch of engineering combining mechanical, electrical and electronics, control and automation, and computer engineering fields. The main research task of mechatronics is design, control, and optimization of advanced devices, products, and hybrid systems utilizing the concepts found in all these fields. The purpose of this special issue is to help better understand how mechatronics will impact on the practice and research of developing advanced techniques to model, control, and optimize complex systems. The special issue presents recent advances in mechatronics and related technologies. The selected topics give an overview of the state of the art and present new research results and prospects for the future development of the interdisciplinary field of mechatronic systems

Fujaba days 2009 : proceedings of the 7th international Fujaba days, Eindhoven University of Technology, the Netherlands, November 16-17, 2009

Fujaba is an Open Source UML CASE tool project started at the software engineering group of Paderborn University in 1997. In 2002 Fujaba has been redesigned and became the Fujaba Tool Suite with a plug-in architecture allowing developers to add functionality easily while retaining full control over their contributions. Multiple Application Domains Fujaba followed the model-driven development philosophy right from its beginning in 1997. At the early days, Fujaba had a special focus on code generation from UML diagrams resulting in a visual programming language with a special emphasis on object structure manipulating rules. Today, at least six rather independent tool versions are under development in Paderborn, Kassel, and Darmstadt for supporting (1) reengineering, (2) embedded real-time systems, (3) education, (4) specification of distributed control systems, (5) integration with the ECLIPSE platform, and (6) MOF-based integration of system (re-) engineering tools. International Community According to our knowledge, quite a number of research groups have also chosen Fujaba as a platform for UML and MDA related research activities. In addition, quite a number of Fujaba users send requests for more functionality and extensions. Therefore, the 7th International Fujaba Days aimed at bringing together Fujaba developers and Fujaba users from all over the world to present their ideas and projects and to discuss them with each other and with the Fujaba core development team