Petri-Nets-Based Controllers Generation Using Genetic Programming

Existing research has shown the effectiveness of genetic strategies in generating Petrin-Net (PN)-based controllers, but limitations exist in the ease of controller generation due to the designer’s ability and the system’s complexity. In the case of automated controller generators based on genetic programming (GP), limitations arise from the static nature of their chromosome over the evolution process. In this short paper we introduce a first discrete PN-based controller designer that can accept systems modeled either continuously or discretely, making it more flexible in handling a wide range of systems. By utilizing genetic algorithms and PNs, the program can generate controllers tailored to the specific requirements of a given system, including the optimal size of the controller. This novel approach has the potential for far-reaching applications in various fields.