Henner Vocking

Self-optimization of an active suspension system regarding energy requirements

Within the collaborative research center 614: ldquoself-optimizing concepts and structures in mechanical engineeringrdquo methods are developed that enable mechatronic systems to adapt to varying environment and system conditions. An important application example is the innovative railcab system that features autonomously driving rail-bound vehicles. These vehicles contain several subsystems to fulfill specific tasks. The subsystems mainly are coupled via their energy demands. Here an approach for optimizing the main task of one subsystem - the active suspension system - is presented. Based on a given global plan for an entire travel a local model-based optimization is done for each track section. The optimization makes use of data about the excitation that is stored locally at the track and can be accessed by the vehicle before arriving at the specific track section. In this way controller configurations can be calculated that maximize the riding comfort while keeping energy constraints from the superposed system.

Tool Support for Developing Advanced Mechatronic Systems: Integrating the Fujaba Real-Time Tool Suite with CAMeL-View

The next generation of advanced mechatronic systems is expected to use its software to exploit local and global networking capabilities to enhance their functionality and to adapt their local behavior when beneficial. Such systems will therefore include complex hard real-time coordination at the network level. This coordination is further reflected locally by complex reconfiguration in form of mode management and control algorithms. We present in this paper the integration of two tools which allow the integrated specification of real-time coordination and traditional control engineering specifically targeting the required complex reconfiguration of the local behavior.

Probabilistic planning integrated in a multi-level dependability concept for mechatronic systems

Self-optimizing mechatronic systems are a new class of technical systems. On the one hand, new challenges regarding dependability arise from their additional complexity and adaptivity. On the other hand, their abilities enable new concepts and methods to improve the dependability of mechatronic systems. This paper introduces a multi-level dependability concept for self-optimizing mechatronic systems and shows how planning can be used to improve the availability and reliability of systems in the operating stages.

Iterative Learning and Self-Optimization Techniques for the Innovative Railcab-System

In this paper, we propose a new concept for information processing of networked vision sensors for surveillance. The networked sensor technology has a potential capability to solve some of our most important scientific and societal problems. But, difficulties of processing are always big problems in case of such huge amount of information acquired by the distributed vision systems. The proposed concept gets a hint from information processing of human hearing organs and compound eyes of insects. By a basic experiment, we confirmed that the proposed concept can be utilized to detect human behavior

Multirate simulation of mechatronic systems

In the simulation of mechatronic systems with the help of computers, the use of multirate integration methods allows saving computing time response reaching higher computing precision without higher expense. In the process, however, effects like aliasing and undesirable high frequencies may occur that can result from differing stepsizes. In the following, we present the mechanisms that can compensate for these negative features. Moreover, an exemplary system is used to describe the partitioning into subsystems of varying velocity. Eventually the simulation results of the subsystem in question are presented and discussed. This paper is structured as follows: Section 1 gives an overview of the contents. Section 2 presents a suitable multirate integration method. Section 3 deals with the sequence of evaluations. Section 4 illustrates the realization by software tools and in Section 5 the method described is shown by an example.