Simulation of self optimizing mechatronical systems with expert system knowledge

Mechatronic systems with autonomous adaptive behavior gain increasing importance. Although modern adaptive controller systems are able to compensate a changing environment, the approach of self-optimization goes further. The basic idea is not to implement a compensation mechanism which ensures the defined dynamic behavior but to optimize the system during runtime. In addition the aims of the optimization themselves will alter. In most cases it is desirable to balance different objectives which could contradict each other. This paper presents an integration approach of knowledge-based systems into a existing design and simulation framework for mechatronic systems. For the prototypical realization we use the expert system CLIPS. The work can be seen as a first step towards a self-optimizing system.