Distributed Online Experience-based Optimization of Mechatronic Systems

W. Dangelmaier, P. Scheideler, E. Münch, and A. Döring (Germany)


Intelligent Multi-agent System, Complex Mechatronic System, Distributed Optimization


Optimization in mechatronic systems is not only restricted to the optimization of internal mechatronic processes based on internal data. In a complex environment a mechatronic system must also use the experiences of other mechatronic systems of the same or similar kind to optimize its own behavior as fast and reliable as possible. If we consider a mechatronic system as an agent we then speak about a multi-agent system. The principles of a multi-agent system together with agent-based controllers are an excellent means to model and implement optimization processes for collaborating mechatronic systems. This paper suggests a distributed optimization of a complex mechatronic system using an intelligent multi agent approach. The example explains how interaction between mechatronic systems can be used for an online optimization of a default comfort trajectory to pass an uneven surface.

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