Neural fuzzy adaptive control for mobile smart objects
Maria A. Butakova, Andrey V. Chernov, Petr S. Shevchuk, Vladimir D. Vereskun · 2018
In this paper, we propose the neural fuzzy adaptive control system suited for mobile smart objects. The classification of hybrid neural networks based on fuzzy neuron models is presented. The hybrid adaptive system architecture consisting of triple neural networks is proposed. Fuzzifying process with rules database creation and fuzzy membership functions definitions are considered. Also learning experiments with proposed architecture have been implemented.