The Feedback Neural Network Application On Thermal System Modeling

Most traditional system identification methods were applied to linear system,and it is still too difficult to solve the problems of non-linear system.Neural network has Characteristics such as non-linear,parallel distributed processing and self-learning which give us a new way on system identification.This paper research on the structure and dynamic memory characteristics of Elman neural network and increased the learning speed by adding new weights connecting the context nodes to the output nodes.Using this approach to identify reheat steam temperature system,we can see that the Elman neural network can identify linear system as good as least square method.Because neural network have the abilities of self-learning and mapping arbitrary non-linear system,the simulation result of non-linear system identification use Elman neural network is nice too.