The work aims to satisfy the functional needs of user groups for intelligent learning desk by optimizing the functional rationality of intelligent learning desk, so as to improve the satisfaction of users to experience the intelligent learning desk.Firstly, by setting up a fuzzy Kano model questionnaire, the information on the functional needs of intelligent learning desk was collected and the key functional indicators were determined. Secondly, the satisfaction coefficients and weights of each functional need were measured by Better-Worse coefficients, and then a function-behavior-structure mapping was carried out according to the FBS model to find out the opportunity points and explore the need rationality. Finally, the interface design and interaction design were conducted to the intelligent learning desk control system. The user satisfaction and weight coefficients of "precise height adjustment", "intelligent course schedule", "online course resources", "intelligent prompt for time-up" and "screen projection function" are relatively high. The satisfaction coefficient and its four quadrant diagram are used to classify the 21 functional needs of the intelligent learning desk into expectation type, charm type, basic type and no-difference type, and the interface of the intelligent control system of the learning desk is designed in combination with FBS model.