Adaptive Control and Simulation of Production Processes Using Temporal Neuro-Fuzzy Petri Net

Complex systems surround people in many industries. In the process of functioning, complex systems need to overcome various difficulties associated with the influence of external factors, peculiarities of the functioning of processes, etc. Complex system is influenced by a complex and rapidly changing set of external conditions, where effective planning and optimization of resources become key success factors, while the possible trajectories of the production of complex technical objects, the employment plan of equipment and personnel, which helps to optimize processes and reduce production costs. The article examines one of the classes of complex systems, and also proposes a method for adaptive control of systems of this class using temporal neuro-fuzzy Petri nets. These networks combine the concepts of Petri nets, a graphical system modeling and analysis tool, with neural networks and fuzzy logic. Considered algorithmic and software for the implementation and support of processes. The proposed method makes it possible to increase the efficiency of a complex system under changing operating conditions. caused by the influence of various factors.