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Introduction to Self-optimization and Dependability

  • Tobias Meyer
  • Claudia Priesterjahn
  • Walter Sextro
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

This chapter gives an introduction to self-optimizing mechatronic systems and the risks and possibilities that arise with these. Self-optimizing mechatronic systems have capabilities that go far beyond those of traditional mechatronic systems. They are able to autonomously adapt their behavior and so react to outer influences, which can originate e.g. from the environment, changed user requirements or the current system status. The basic process of self-optimization, the procedures employed within and the main components of a self-optimizing system are explained here.

However, during the development of such a system, several challenges need to be met. On this note, both the concept of dependability and our proposed development process for self-optimizing systems are introduced. This process is used to derive a methodology for the selection of dependability methods in the development of self optimizing systems.

To illustrate the proposed process and methods, several demonstrators are introduced. These are self-optimizing systems from different fields of engineering, e.g. robotics, automotive engineering and railroad engineering.

The chapter concludes with an overview of the content of the remainder of the book.

Keywords

Multiobjective Optimization Multiobjective Optimization Problem Active Suspension Mechatronic System Pareto Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Tobias Meyer
    • 1
  • Claudia Priesterjahn
    • 2
  • Walter Sextro
    • 1
  1. 1.Mechatronics and DynamicsUniversity of PaderbornPaderbornGermany
  2. 2.Software Engineering Group, Heinz Nixdorf InstituteUniversity of PaderbornPaderbornGermany

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