Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 1035–1042 (2018)
Abstract. This paper presents a novel approach to synthesise hybrid controllers. A two-phase multi-objective evolutive algo- rithm was used to generate Unified Enhanced Timed Petri Net (UETPN) models. These models combine capabilities of timed Petri-nets, fuzzy logic systems and simple arithmetic operators. They can handle both event-like and continuous inputs (and outputs). The first phase of the algorithm uses Koza style genetic programming combined with multi-objective methods such as NSGA-II and SPEA2 to obtain an initial model. The second phase improves the initial model with recombining the fuzzy rules with genetic algorithm GA. In order to generate UETPN models (with GP), an intermediate language was designed, called UETPN Lisp. Four example are presented to exemplify the potential of the proposed framework.
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