Multi-objective decision making using fuzzy discrete event systems: A mobile robot example

In this paper, we propose an approach for the multi-objective control of sampled data systems that can be modeled as fuzzy discrete event systems (FDES). In our work, the choice of a “fuzzy” system representation is justified by the assumption of a controller realization that depends on various potentially imprecise sensor measurements. Our approach consists of three basic steps that are performed in each sampling instant. First, the current fuzzy state of the system is determined by a sensor evaluation. Second, the future fuzzy state is predicted for the possible control actions, and finally, a particular multi-objective weighting strategy allows to determine the control action to be applied. We demonstrate the features of our method by a mobile robot example.