The Application Of BP Multilayer-NN In Control

The neural network has many abilities: parallel processing, self-learning and self-adapting, approaching any nonlinear function etc. ; to deal with the problem of control in the industry process with wide lag?nonlinear?multivariable and uncertainty, it is an effective way to develop neural network. So neural network is used widely in these aspects: identification, control, parameter optimization.The research of this dissertation lies on three aspects: identification, control, parameter optimization. Firstly this dissertation introduces the design of neural network control system. According to the design, we program the neural network software. The software includes many kinds of networks, and can run with different configration software through different ways. With this software, we can construct the control system. Then we use some networks to identify the furnace. Comparingthe results, a conclusion can be drew: To identify the dynamic system , elman network can get better result. After that, BP neural network is used to optimize the parameters of PID controller, and the controller is also applied to the control of furnace temperature. Then we improved the system with model. At last, we use PID neural network to control the objects directly. The result of the control in three-tank liquid level equipment and stand-up furnace is excellent.The researches above indicate that the neural network can solve the complicated problem of control to a certain extent, and has better prospect in the application of control.