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For unsupervised learning network unsupervised learning network model for a specific mapping space, expect a specific impact has some limitations, supervised can grow structure network dynamic structure model. The model will combine unsupervised learning network model and radial basis function network architecture, uses a growth of self-organizing algorithm when necessary, by inserting a new connections between neurons, change the competitive layer neurons and adjust the weights between layer and layer, meet the requirements of the precision of the model output, effectually solved that when the input is specific network data, can produce the desired output. The model is applied to two rounds of the balancing of the robot control, through the simulation experiments show that, dynamic structure model model realized with two rounds of balance control of the robot, and has certain anti-interference and practical value.