Neuro-fuzzy approach for implementing control systems is considered. Neuro-fuzzy systems are a tool for a development of trainable control systems with high interpretability. These systems can be trained to work in new conditions. There is a possibility to analyze the actions, which implement the control. Examples of neuro-fuzzy control applications are presented: virtual assistant and automatic calibration system.