Dynamic Structure Optimization Neural Network and Its Applications to Dissolved Oxygenic(DO) Control

A dynamic structure optimization design method is proposed for the neural network.This dynamic structure optimization neural network(DSONN) can add or prune the hidden nodes based on the competition mechanism which estimate the influence of hidden nodes on the network output in the learning process.Then it can adjust the architecture of neural network automatically.In the end,the proposed DSONN is used to control the DO concentration in the wastewater treatment processes.The simulation results compared with the fixed structure neural network controller suggest that the proposed DSONN is more effective in the overshoot,the adjusting time and the self-adaptability.